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application engineer

LM Studio

<div><h2 class="jobSectionHeader">The Role</h2>
We're looking for a talented, hungry, and technically excellent Application Engineer to join our team.
In this role you will dream up, build, and ship LM Studio features to millions of users worldwide, at a fast clip. You will be intermixing UI work with systems engineering, design, and applied AI / agentic engineering work.
You may be a good fit if you love building software products, have an innate talent for crafting product experiences, and you approach technical problems with a scientific method mindset. Holistic understanding of software systems and the ability to work across the stack is a must. Experience building desktop applications is a big plus, but not required.
This role is in-person in our New York City office. Relocation assistance is possible. In your application, please share technical details about your expertise and things that you've built.
Relevant experience: React, TypeScript, Electron, Swift, Objective-C, C++.<h2 class="jobSectionHeader">
LM Studio</h2>
We aim to build delightful and potent creation tools for AI. We are a small team based in New York. Everyone on the team is IC-minded, intellectually curious, self-motivated, and loves software. We care deeply about our user community and we strive to build canonical software that users and developers love.<h2 class="jobSectionHeader">
Our Interview Process</h2>
We are looking for engineering excellence and strong values / cultural fit. If your application appears to be a good match we'll reach out to schedule an initial call. If all goes well, we will proceed to 2-3 technical interviews. The final step in the process is an onsite interview in our New York office, where you will work through several more technical sessions focused around system design and architecture, meet the team and see how we work.
Compensation Range: $175K - $275K</div>

Application Engineer

Morgan Stanley

<div>In the Technology division, we leverage innovation to build the connections and capabilities that power our Firm, enabling our clients and colleagues to redefine markets and shape the future of our communities.
This is a Lead Software Production Management &amp; Reliability Engineering position at Director level which is part of the job family responsible for overseeing the production environment, ensuring the operational reliability of deployed software, and implementing strategies to optimize performance and minimize downtime.
Since 1935, Morgan Stanley has been known as a global leader in financial services, always evolving and innovating to better serve our clients and our communities in more than 40 countries around the world.
Department Profile
Morgan Stanley Wealth Management (MSWM) Technology is the global technology department responsible for the design, development, delivery and support of the technical solutions behind the products and services used by the Morgan Stanley Wealth Management (MSWM) business. The department is comprised of 10 organizations: Sales, Banking &amp; Corporate-Client Technology, Investment Products &amp; Markets Technology, Client Reporting, Core Processing, Private and International Wealth Management Technology, Technology Integration Office, Enterprise Infrastructure &amp; Production Management, Capital Markets Application &amp; Data Services, Deployment Planning &amp; Release Management, and the Chief Operating Office.
The Reliability Operations (RO) within WMT is responsible for providing swift, courteous, and knowledgeable customer service to end users of the production systems. This position is focused on user and systems support, answering hotline calls, monitoring systems alerts, and taking corrective action. Technical understanding is important as well as the ability to speak to users and understand their problems. In addition to direct user support tasks, the team performs infrastructure related tasks including process configuration, hardware capacity planning, event management, release work, and support tool development to ensure any repetitive tasks are packaged to remove any element of risk.
Position Overview
The Wealth Management Production Management Site Reliability Engineer position is a highly visible/critical role, which will be a team member of technical SME&rsquo;S managing the stability and optimization of the Wealth Management systems. Scope includes but not limited to, the day-to-day support of the organization&rsquo;s technology related outages, collaboration on technology projects
focused on stability, optimization, business impact analysis, and associated risk-related methodologies. This role will be responsible for overall stability of the Wealth Management Investment Management application platforms, participation on key optimization initiatives, and collaboration with multiple technical teams within Morgan Stanley. Additionally, partners with WM business units, various levels of management and staff to collect, analyze and make recommendations on optimizing the platform.
As a team member with expertise in deep analytical triage, you will provide subject matter expertise in debugging, issue analysis and troubleshooting, working with business and technical colleagues to provide reviews and recommendations to avoid any future application issues. Produce guidance documentation, standards and procedures, products assessments, and training material including working with the various application and infrastructure support teams ensuring that they are documenting every single troubleshooting step in Morgan Stanley knowledge base system to resolve issues in a faster time frame. You will serve as a fully seasoned/proficient technical resource; provide technical knowledge in outage management and proactive solutions to improve the user experience.
This position will mainly perform DevOps/ SRE role in Application support, Platform Stability and Resiliency.
Role &amp; Responsibilities:
<ul><li>Proactively detecting, troubleshooting, and resolving all issues affecting production applications. This involves coordination with and escalation to development and external teams where necessary. This team owns all issues escalated to us until it is resolved or a workaround is provided for end users to continue functioning.
</li><li>Responsible for maintaining clear, concise, and timely communications with affected parties during the investigation and resolution of any individual or system-wide outage
</li><li>Responsible for the stability of the Production environment
</li><li>Develop and continually revise in partnership with other teams where necessary) suitable policies and procedures to ensure appropriate application development standards are available to guide development for systems deployed to Production.
</li><li>As the gatekeepers of the Production environment, responsible for ensuring the Change Implementation Management guidelines/policies are adhered to for all systems deployed to Production.
</li><li>Responsible for servicing all requests for data or other activities that require access to Production systems
</li><li>Work with development teams at the appropriate stages in application development to ensure any new systems or projects meet the Production standard
</li><li>Responsible for maintaining and growing a body of knowledge that is accessible to all team members. Ensure information regarding any support related activities or issues are available and easily accessible. The goal is to improve self-reliance and reduce dependency on the availability of development or external team resources for the initial troubleshooting and resolution of problems.
</li></ul>Primary skills
<ul><li>Minimum 5&ndash;7 years of experience developing and/or supporting enterprise applications
</li><li>3&ndash;5 years of experience leading a small-to-medium team with similar skill sets
</li><li>Willingness to embrace Agile practices and DevOps/SRE concepts
</li><li>Working knowledge of DevOps and observability tools (e.g., Grafana, Prometheus, Splunk, Kibana)
</li><li>Strong analytical skills, including problem determination and recovery/resolution processes
</li><li>Ability to interface with and build strong working relationships across technology teams, business analysts, and vendors
</li><li>Understanding of database engineering and the ability to develop high-quality database solutions
</li><li>Experience with AWS services such as EC2, ECS, S3, Fargate, Aurora, and Lambda
</li><li>Hands-on scripting experience with Python and working knowledge of Java
</li><li>Administrative competence in at least one major programming language or platform (e.g., Perl, PowerShell, Unix scripting, Java, C#, .NET)
</li><li>Exposure to application technologies such as JavaScript, React, GraphQL, Python, Django, Celery, PostgreSQL, Golang, ElasticSearch, RabbitMQ and Kafka.
</li><li>Experience with web analytics tools (preferably Adobe Experience Cloud) is a plus
</li><li>Fast learner who thrives in a fast-paced environment
</li><li>Strong organizational skills and the ability to manage multiple tasks and high-pressure outage situations through resolution
</li><li>Driven to learn new technologies and techniques and to be an integral member of the team
</li><li>Hands-on experience administering large-scale, high-availability systems and using tools to monitor performance and availability
</li><li>Experience in creating technical architecture documentation
</li><li>Excellent written and verbal communication skills for technical discussions across management layers
</li><li>BS/MS degree (or equivalent), preferably in a quantitative discipline (e.g., Computer Science, Computer Engineering)
</li><li>Experience with on-call support and the ability to respond to emergencies on a 24/7 basis
</li><li>Experience in the financial services industry is a plus
</li><li>Assist with investigating and troubleshooting production issues, and actively mentor/coach/train team members
</li></ul>Secondary Skills
<ul><li>5&ndash;10 years of experience supporting or developing transaction-based systems
</li><li>Hands-on technical professional who understands both code and infrastructure
</li><li>Proven operational/support background with strong understanding of incident, problem, and change management to drive stability across organizations
</li><li>Ability to lead outage incidents by coordinating cross-team response and user communications through resolution
</li><li>Strong focus on metrics, monitoring, and trend analysis
</li><li>Strong problem-solving skills with the ability to analyze and interpret data
</li><li>Ability to build strong relationships and coordinate effectively with multiple parties during outages, while providing clear updates to APG and BU partners
</li><li>Comfortable with an on-call rotation, including weekend work
</li><li>Strong end-user support skills; able to partner with users to diagnose issues and drive to resolution
</li><li>Self-motivated with excellent written and verbal communication; able to communicate clearly and concisely
</li><li>Strong ownership mentality with a focus on customer satisfaction
</li><li>Detail-oriented and well organized, with strong analytical skills
</li><li>Experience working in a virtual and/or global team environment
</li><li>Self-starter with a &ldquo;can-do&rdquo; attitude and the ability to multitask effectively
</li><li>Familiarity with ITIL concepts, especially incident and problem management
</li></ul>We have a track record of innovation and passion for unlocking new opportunities, we help our clients raise, manage and allocate capital. We do this by offering a wide range of investment banking, securities, wealth management and asset management services.
All that we do at Morgan Stanley is driven by our five core values: do the right thing, put clients first, lead with exceptional ideas, commit to diversity and inclusion, and give back. These aren&rsquo;t just beliefs, they guide the decisions we make every day, ensuring we do what's best for our clients, communities and more than 80,000 employees around the world. And at the core of our success are the people who drive it - relentless collaborators and creative thinkers who are fueled by diverse thinking and experiences.
Wherever you are in our 1,200 global offices, you&rsquo;ll have the opportunity to work alongside the best and the brightest in an environment where you are empowered to achieve your full potential. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry.
Morgan Stanley's goal is to build and maintain a workforce that is diverse in experience and background but uniform in reflecting our standards of integrity and excellence. Consequently, our recruiting efforts reflect our desire to attract and retain the best and brightest from all talent pools. We want to be the first choice for prospective employees.
It is the policy of the Firm to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, creed, age, sex, sex stereotype, gender, gender identity or expression, transgender, sexual orientation, national origin, citizenship, disability, marital and civil partnership/union status, pregnancy, veteran or military service status, genetic information, or any other characteristic protected by law.
Morgan Stanley is an equal opportunity employer committed to diversifying its workforce (M/F/Disability/Vet).
WHAT YOU CAN EXPECT FROM MORGAN STANLEY:
At Morgan Stanley, we raise, manage and allocate capital for our clients &ndash; helping them reach their goals. We do it in a way that&rsquo;s differentiated &ndash; and we&rsquo;ve done that for 90 years. Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren&rsquo;t just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, you&rsquo;ll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There&rsquo;s also ample opportunity to move about the business for those who show passion and grit in their work.
To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices into your browser.
Expected base pay rates for the role will be between $120,000 and $165,000 per year at the commencement of employment. However, base pay if hired will be determined on an individualized basis and is only part of the total compensation package, which, depending on the position, may also include commission earnings, incentive compensation, discretionary bonuses, other short and long-term incentive packages, and other Morgan Stanley sponsored benefit programs.
Morgan Stanley is an equal opportunity employer committed to building and maintaining a workforce that is diverse in experience and background. Our recruiting efforts reflect our strong commitment to a culture of inclusion, where individuals are hired, developed, and advanced based on their skills and talents.
Our workforce reflects a broad cross-section of the global communities in which we operate, bringing a variety of backgrounds, talents, perspectives, and experiences.
For more information, please visit : https://www.morganstanley.com/people-opportunities/eeo .</div>

SRE Application Support Engineer - AWS

Invio Automation

<div>
 
 The Company
 
 
 
 Invio Automation is a leading provider of advanced automation solutions, serving high-growth markets including medical device and life sciences, renewable energy, mobility, logistics &amp; fulfillment, and heavy industry. Our collaborative teams deliver mission-critical R&amp;D pre-validation services that lay the foundation for full-scale automation systems&mdash;where precision, efficiency, and accuracy are essential to success. With six locations across North America and a global network of partners, Invio maintains a strong presence in key regions where local service and support matter.
 
 
 Invio&rsquo;s proven portfolio of Industry 4.0 technology includes Autonomous Guided Vehicles (AGVs) for heavyweight applications, turnkey assembly lines, welding automation, lift-assist tools for safety-critical operations, robotic cells, multi-station assembly systems, bonding and welding technologies, vision systems, and precision dispensing solutions such as high-viscosity pumps, impulse bag sealing, and needle bending.
 
 
 Working at Invio means making a direct impact on the future of American manufacturing. We are committed to improving the lives of those who partner with us by designing and integrating custom-engineered automation solutions that enhance safety, increase efficiency, and raise product quality for our customers.
 
 
 
 Description
 
 
 
 The Applications Engineer supports the front-end development of automation solutions by collaborating with mechanical and controls engineers to validate system concepts and prepare customer-focused proposals. This role focuses on learning to interpret customer requirements, RFQs, and application needs while developing foundational skills in system concepts, estimating, documentation, and proposal development. Working under general supervision, the Applications Engineer assists in preparing technical content, CAD layouts, cost inputs, and supporting documentation while gaining hands-on exposure to automation system components and how they integrate into customer processes. This role plays a key part in supporting feasibility studies, proposal accuracy, and cross-functional alignment.
 
 
 
 Responsibilities
 
 
 
 
 ESSENTIAL DUTIES AND RESPONSIBILITIES
 
 
 
 <ul>
 <li>
 Serve as the technical authority and Subject Matter Expert for application development, ensuring customer solutions reflect best practices, innovation, scalability, and Invio standards.
 </li>
 <li>
 Analyze customer RFQs, specifications, concepts, and drawings to extract key requirements and estimating inputs.
 </li>
 <li>
 Assist in preparing system concepts, application notes, CAD layouts, and cost estimates under guidance from senior engineers.
 </li>
 <li>
 Support proposal preparation by gathering BOM data, drawings, and supporting documentation.
 </li>
 <li>
 Perform data collection, basic testing, and documentation to support application feasibility studies.
 </li>
 <li>
 Respond to internal and external information requests related to customer proposals and concepts.
 </li>
 <li>
 Observe and support customer meetings under the guidance of senior engineers.
 </li>
 <li>
 Collaborate cross-functionally with sales, engineering, and operations to align proposed solutions with customer expectations.
 </li>
 <li>
 Document technical findings clearly and accurately using Excel, PowerPoint, and written reports.
 </li>
 <li>
 Track assigned tasks and deadlines, escalating questions or risks as appropriate.
 </li>
 <li>
 Other duties as assigned
 
 
 
 </li>
 </ul>
 
 Qualifications:
 
 
 
 <ul>
 <li>
 5&ndash;10 years of relevant experience in automation, manufacturing, applications engineering, or a related technical role
 </li>
 <li>
 Experience reviewing customer RFQs, drawings, or technical specifications
 </li>
 <li>
 Familiarity with automation system components, including mechanical, controls, and robotics concepts
 </li>
 <li>
 Strong organizational skills with attention to detail and accuracy
 </li>
 <li>
 Ability to communicate clearly with engineers, sales, and operations teams
 
 
 
 </li>
 </ul>
 
 Other Skills and Abilities:
 
 
 
 <ul>
 <li>
 Excellent interpersonal, negotiation, problem-solving, and conflict-resolution skills
 </li>
 <li>
 Excellent organizational skills and attention to detail
 </li>
 <li>
 Excellent time management skills with a proven ability to meet deadlines
 </li>
 <li>
 Ability to act with integrity, professionalism, and confidentiality
 </li>
 <li>
 Proficient with Microsoft Office Suite or related software
 </li>
 <li>
 Proficiency with or the ability to quickly learn the organization&rsquo;s ERP, and Salesforce system
 </li>
 <li>
 Strategic thinker with the ability to translate business objectives into Invio&rsquo;s sales initiatives
 </li>
 <li>
 Willingness to travel within North America, up to 15% of the time
 
 
 
 </li>
 </ul>
 
 EDUCATION
 
 
 
 Associate&rsquo;s degree required in Engineering Technology, Manufacturing, or a related technical field. Bachelor&rsquo;s degree in Engineering, Manufacturing, or a related field preferred
 
 
 
 INVIO AUTOMATION&rsquo;S CORE VALUES
 
 
 
 <ul>
 <li>
 We take pride in the reliability of our team and the difficult problems we solve for customers.
 </li>
 <li>
 We deliver real customer value that positively impacts the lives of those around us.
 </li>
 <li>
 We are dependable. Relationships and trust matter.
 </li>
 <li>
 Our ingenuity and desire to improve lives will complement our suite of solutions.
 </li>
 <li>
 We strive to demonstrate that our attention to detail does not start or end with the solutions we engineer and deliver.
 </li>
 <li>
 We believe exceptional service is better demonstrated than said.
 </li>
 </ul>
</div>

Applications Engineer - Robotics / Weld Tooling

Asana

<div>The Mobile team's mission is to enable teams to work together effortlessly, even when they are away from their desktops. We partner closely with Product Designers, PMs, and other product engineering teams to continuously improve the Asana experience for our customers on-the-go. We work hard to maintain a codebase and a culture that is a joy to work in by combining mobile best practices with many of the innovative opportunities that our in-house frameworks provide.

Software Engineers at Asana are quickly trusted to own major parts of both the codebase and our processes through the Areas of Responsibility system. We expect you to thrive in defining and solving problems, with mutual support from your peers.

This role is based in our New York City office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. If you're interviewing for this role, your recruiter will share more about the in-office requirements.

What you'll achieve:
<ul>
<li>Ship fast and deliver high-quality experiences to our global users in close collaboration with Product and Design partners.</li>
<li>Elevate engineering standards through strategic technical investments, delivering improved code quality, expanded test coverage, and reduced technical debt.</li>
<li>Craft well-documented, well-structured, and well-tested code.</li>
<li>Help the team improve by providing thoughtful feedback in code/design reviews and mentoring others.</li>
<li>Accelerate Asana's Mobile teams by leveraging the latest practices, tooling and SDKs.</li>
<li>Own and contribute to AoRs (Areas Of Responsibility).</li>
</ul>
About you
<ul>
<li>3+ years of experience developing, releasing, and maintaining high-quality iOS applications, ideally using Swift.</li>
<li>Aware of the latest developments in the iOS ecosystem.</li>
<li>Advocate for leaving code better than you found it.</li>
<li>Passion for crafting a delightful end-user experience.</li>
<li>Commitment to continuous improvement and mentorship.</li>
<li>Good judgment for balancing scrappiness and long-term code maintainability.</li>
<li>Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making.</li>
</ul>
At Asana, we're committed to building teams that include a variety of backgrounds, perspectives, and skills, as this is critical to helping us achieve our mission. If you're interested in this role and don't meet every listed requirement, we still encourage you to apply.

What we'll offer

Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit.

For this role, the estimated base salary range is between $171,000- $190,000. The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified.

In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.

We strive to provide equitable and competitive benefits packages that support our employees worldwide and include:
<ul>
<li>Mental health, wellness &amp; fitness benefits</li>
<li>Career coaching &amp; support</li>
<li>Inclusive family building benefits</li>
<li>Long-term savings or retirement plans</li>
<li>In-office culinary options to cater to your dietary preferences</li>
</ul>
These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.

#LI-Hybrid<div>
About us

Asana is a leading platform for human + AI collaboration. Millions of teams around the world rely on Asana to achieve their most important goals, faster. Asana has been named to Fortune's Best Workplaces for 7+ years and recognized by Fast Company, Forbes, and Gartner for excellence in workplace culture and innovation. We offer an exceptional office-centric culture while adopting the best elements of hybrid models to ensure that every one of our global team members can work together effortlessly. With 13+ offices all over the world, we are always looking for individuals who care about building technology that drives positive change in the world and a culture where everyone feels that they belong.

Join Asana's Talent Network to stay up to date on job opportunities and life at Asana.</div></div>

Mobile Engineer, iOS

Information Technology Senior Management Forum

<div><div>Posted Date
4/10/2026
</div><div>Description
<div>Senior Lead Machine Learning Engineer
As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You&rsquo;ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You&rsquo;ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.
What you&rsquo;ll do in the role:
The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:<ul><li>
Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams.</li><li>
Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).</li><li>
Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.</li><li>
Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.</li><li>
Retrain, maintain, and monitor models in production.</li><li>
Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.</li><li>
Construct optimized data pipelines to feed ML models.</li><li>
Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.</li><li>
Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.</li><li>
Use programming languages like Python, Scala, or Java.</li></ul>
Basic Qualifications:<ul><li>
Bachelor&rsquo;s Degree</li><li>
At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)</li><li>
At least 4 years of experience programming with Python, Scala, or Java</li><li>
At least 3 years of experience building, scaling, and optimizing ML systems</li><li>
At least 2 years of experience leading teams developing ML solutions</li></ul>
Preferred Qualifications:<ul><li>
Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field</li><li>
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform</li><li>
4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, Kubeflow or TensorFlow</li><li>
3+ years of experience developing performant, resilient, and maintainable code</li><li>
3+ years of experience with data gathering and preparation for ML models</li><li>
ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents</li><li>
3+ years of experience building production-ready data pipelines that feed ML models</li><li>
Ability to communicate complex technical concepts clearly to a variety of audiences</li></ul>
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
Cambridge, MA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer 

McLean, VA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer 

New York, NY: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer 

San Francisco, CA: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer 

San Jose, CA: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer 
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate&rsquo;s offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City&rsquo;s Fair Chance Act; Philadelphia&rsquo;s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Senior Lead Machine Learning Engineer
As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You&rsquo;ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You&rsquo;ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.
What you&rsquo;ll do in the role:
The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:<ul><li>
Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams.</li><li>
Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).</li><li>
Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.</li><li>
Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.</li><li>
Retrain, maintain, and monitor models in production.</li><li>
Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.</li><li>
Construct optimized data pipelines to feed ML models.</li><li>
Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.</li><li>
Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.</li><li>
Use programming languages like Python, Scala, or Java.</li></ul>
Basic Qualifications:<ul><li>
Bachelor&rsquo;s Degree</li><li>
At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)</li><li>
At least 4 years of experience programming with Python, Scala, or Java</li><li>
At least 3 years of experience building, scaling, and optimizing ML systems</li><li>
At least 2 years of experience leading teams developing ML solutions</li></ul>
Preferred Qualifications:<ul><li>
Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field</li><li>
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform</li><li>
4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, Kubeflow or TensorFlow</li><li>
3+ years of experience developing performant, resilient, and maintainable code</li><li>
3+ years of experience with data gathering and preparation for ML models</li><li>
ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents</li><li>
3+ years of experience building production-ready data pipelines that feed ML models</li><li>
Ability to communicate complex technical concepts clearly to a variety of audiences</li></ul>
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
Cambridge, MA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer 

McLean, VA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer 

New York, NY: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer 

San Francisco, CA: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer 

San Jose, CA: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer 
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate&rsquo;s offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City&rsquo;s Fair Chance Act; Philadelphia&rsquo;s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).</div>
</div><div>Salary
229,900.00 - 262,400.00 Annual
</div><div></div><div><div>Type<div>
Full-time</div></div></div></div>

Senior Lead Machine Learning Engineer

Capital One

<div>Senior Lead Machine Learning Engineer
As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You&rsquo;ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You&rsquo;ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.
What you&rsquo;ll do in the role:
The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:<ul><li>
Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams.</li><li>
Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).</li><li>
Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.</li><li>
Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.</li><li>
Retrain, maintain, and monitor models in production.</li><li>
Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.</li><li>
Construct optimized data pipelines to feed ML models.</li><li>
Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.</li><li>
Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.</li><li>
Use programming languages like Python, Scala, or Java.</li></ul>
Basic Qualifications:<ul><li>
Bachelor&rsquo;s Degree</li><li>
At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)</li><li>
At least 4 years of experience programming with Python, Scala, or Java</li><li>
At least 3 years of experience building, scaling, and optimizing ML systems</li><li>
At least 2 years of experience leading teams developing ML solutions</li></ul>
Preferred Qualifications:<ul><li>
Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field</li><li>
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform</li><li>
4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, Kubeflow or TensorFlow</li><li>
3+ years of experience developing performant, resilient, and maintainable code</li><li>
3+ years of experience with data gathering and preparation for ML models</li><li>
ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents</li><li>
3+ years of experience building production-ready data pipelines that feed ML models</li><li>
Ability to communicate complex technical concepts clearly to a variety of audiences</li></ul>
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
Cambridge, MA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer 

McLean, VA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer 

New York, NY: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer 

San Francisco, CA: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer 

San Jose, CA: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer 
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate&rsquo;s offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.
No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City&rsquo;s Fair Chance Act; Philadelphia&rsquo;s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).</div>

Amazon

<div>
 
 Description
 
 
 
 Amazon is seeking an Automation Operations Engineer to support the Amazon Logistics North America (AMZL NA) Core Operations Engineering team. This individual will be responsible for designing and managing the next generation of delivery station processes, equipment, and operations. As a Operations Engineer for Amazon, the individual will be able to work with some of the most talented engineers in the design, development, and delivery of systems around the globe. This role will be responsible to lead initiatives and complex cross-functional projects or programs in ambiguous and complex problem spaces.
 
 
 Key job responsibilities
 
 
 <ul>
 <li>
 Integrate systems for safety, security, stability, and efficiency
 </li>
 <li>
 Participate in the full system development life-cycle, working within broadly defined parameters, including test plan execution and solution quality needs
 </li>
 <li>
 Manage multiple high-visibility projects and tasks while effectively influencing, negotiating, and communicating with internal and external business partners, integrators, and vendors to generate high-quality, cost-effective automation solutions in support of business objectives
 </li>
 <li>
 Define projects (scope, delivery, and budget), set objectives, analyze data, drive improvements to metrics, and influence resource allocation
 </li>
 <li>
 Deep dive technical solutions that encompass advanced technology applications, conveyor hardware selection, automation integration, and vendor commissioning content and expectations
 </li>
 <li>
 Lead and coordinate design and execution efforts between internal teams and outside vendors including equipment specifications, material flow, process design, and site layout
 </li>
 <li>
 Lead and actively participate in design reviews and communicate future impacts of proposed solutions on an individual system and on the overall facility processes
 </li>
 <li>
 Build relationships with partner organizations within the company such as Start-up, Design team, Procurement, Tech, Safety, Change Management, RME and Operations
 </li>
 <li>
 Identify and lead process improvement initiatives in support of operations teams
 </li>
 <li>
 Develop cross-functional knowledge of Operations and Engineering team systems, processes, procedures, and tools
 </li>
 <li>
 Travel approximately 75% of the time
 
 
 </li>
 </ul>
 
 Basic Qualifications
 
 
 
 <ul>
 <li>
 Bachelor's degree
 </li>
 <li>
 Knowledge of Microsoft Office products and applications (Excel, PowerPoint, Word, Visio, and MS Project) at an advanced level
 </li>
 <li>
 3+ years of industrial engineer, operations engineer, manufacturing engineer, or project engineer in a manufacturing environment experience
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience with Six Sigma, lean manufacturing
 </li>
 <li>
 Experience Experience working with Material handling equipment (MHE)
 </li>
 <li>
 Knowledge of AutoCAD, VBA, and SQL at the intermediate level
 </li>
 <li>
 Knowledge of automated material handling systems, packaging technologies and storage solutions
 </li>
 <li>
 Master's degree
 
 
 </li>
 </ul>
 Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
 
 
 Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
 
 
 Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
 
 
 Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.
 
 
 Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $68,900/year in our lowest geographic market up to $126,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
 
 
 
 
 Company
 
 - Amazon.com Services LLC
 
 
 Job ID: A3052142
</div>

Operations Engineer, Automation Operations Engineering

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