software engineer

ai engineer

ai engineer ii

backend engineer

engineer

systems engineer

Mirage

<div>Mirage is an AI-native video platform that intelligently orchestrates production and editing through natural language. Our models leverage contextual awareness to execute the same creative decisions a professional editor would &mdash; dramatically improving productivity for experienced teams, while making video creation accessible to anyone. 
 
We&rsquo;re an interdisciplinary team addressing some of the most difficult technical and creative challenges in generative media. As an early member of our team, you&rsquo;ll tackle foundational problems that remain largely unsolved across the industry, driving an outsized impact on the future of creative expression. 
More about us
Product (Captions by Mirage)
Research (Seeing Voices, technical-white-paper)
Updates (Mirage on X / twitter)
TechCrunch, Forbes AI 50, Fast Company (press) 
Our Investors
We&rsquo;re very fortunate to have some the best investors and entrepreneurs backing us, including Index Ventures, Kleiner Perkins, Sequoia Capital, Andreessen Horowitz, General Catalyst, Uncommon Projects, Kevin Systrom, Mike Krieger, Lenny Rachitsky, Antoine Martin, Julie Zhuo, Ben Rubin, Jaren Glover, SVAngel, 20VC, Ludlow Ventures, Chapter One, and more.
Please note that all of our roles will require you to be in-person at our NYC HQ (located in Union Square)
About the Role 
Mirage is seeking an ML Engineer to push the boundaries of large language models for multimodal creative tasks. You'll develop new approaches for building and extending agentic systems that understand and operate over complex, real-world data, particularly video.
This role focuses on advancing agent capabilities, improving reasoning and control, and enabling new forms of interaction between language models and time-based media.
Responsibilities<ul><li>
Design and build end-to-end agentic systems for creative tasks</li><li>
Develop novel approaches for training and adapting the large language models that power these agents</li><li>
Design new objectives, datasets, and fine-tuning strategies to improve agent behavior and reliability</li><li>
Explore multimodal reasoning and structured generation for creative control</li><li>
Run systematic experiments to evaluate and improve agent performance in real-world tasks</li><li>
Design evaluation frameworks for agentic workflows in video analysis and editing</li><li>
Analyze failure modes across the full agent loop (planning, tool use, execution) and iterate on improvements</li></ul>
What makes you a great fit<ul><li>
BS/MS/PhD in CS, ML, or related field</li><li>
Strong track record building production ML systems or agentic pipelines</li><li>
Deep understanding of transformers and modern LLM techniques</li><li>
Experience with fine-tuning, alignment, or post-training methods, especially for adapting models to generate structured outputs or drive tool use</li><li>
Comfort owning the full stack, from model-level experiments to deployed agent systems</li><li>
Strong experimental rigor and good taste for what makes agents actually work in practice</li></ul><h3 class="jobSectionHeader">
Benefits:</h3><ul><li>
Comprehensive medical, dental, and vision plans</li><li>
401K with employer match</li><li>
Commuter Benefits</li><li>
Catered lunch multiple days per week</li><li>
Dinner stipend every night if you're working late and want a bite!
</li><li>Grubhub subscription</li><li>
Health &amp; Wellness Perks</li><li>
Multiple team offsites per year with team events every month</li><li>
Generous PTO policy</li></ul>
Captions provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
Please note benefits apply to full time employees only.
Compensation Range: $175K - $275K</div>

Research Engineer, Agentic Systems

Elliptic

<div>Do you want to help define the future of finance?
Are you a strong software engineer who's passionate about data, distributed systems, and delivering impact at scale? Are you looking for a values-driven company that invests in its people and gives you the autonomy to shape critical systems, while staying close to the code?
We're looking for a Senior Software Engineer to join Elliptic's Product-Engineering organisation, focusing on data engineering solutions that power our blockchain analytics and intelligence products. This is a hands-on engineering role: as a senior member of the team, you will spend the majority of your time designing, building, and shipping the data platform yourself, while driving the technical direction that ensures it continues to meet the growing demands of blockchain analysis.
Challenges include building a blockchain-agnostic solution that scales globally, processing large batch and streaming datasets, and solving complex data processing problems that give our customers deep insights into the flow of value across the crypto ecosystem.<h2 class="jobSectionHeader"> 
The impact you will have</h2>
Our data and intelligence platform sits at the heart of everything we do. As a senior engineer, you will personally design and build data systems that serve as the backbone of all Elliptic products. By collaborating across blockchain, intelligence and product teams, you will deliver innovative features that help the world fight financial crime and increase transparency in the crypto space. Very few engineering roles have such clearly measurable real-world impact.
You will also help us excel in engineering excellence by mentoring and upskilling our highly-engaged and passionate engineers, by championing best practices, and holding yourself and your team to a high standard.<h2 class="jobSectionHeader"> 
What you will do</h2><ul><li>
Write, ship, and maintain production code as a hands-on engineer.</li><li>
Architect, design, and implement large-scale distributed data systems and pipelines.</li><li>
Contribute to technical decision-making across batch and streaming data solutions.</li><li>
Collaborate with engineers, product managers, data scientists, and intelligence analysts to build customer-focused products.</li><li>
Explore and integrate new technologies (e.g. data orchestration or cloud-native tools) to optimise performance and scalability.</li><li>
Take shared ownership of data systems, from design to deployment and ongoing improvement and support.</li><li>
Perform thoughtful peer reviews that raise code quality and share best practices across the team.</li><li>
Contribute to platform-wide initiatives that improve reliability, observability, and cost efficiency.</li><li>
Help shape the technical roadmap for data engineering across Elliptic.</li><li>
Leverage and deploy AI and agentic systems to operate more effectively.</li></ul><h2 class="jobSectionHeader"> 
Tech environment</h2>
Scala | Spark | Databricks | AWS | Airflow | Kubernetes | Terraform | Functional Programming<h2 class="jobSectionHeader">
You will thrive here if you</h2><ul><li>
Enjoy end-to-end ownership, from writing the code to architecture design to coaching others through delivery.</li><li>
Strive for engineering excellence and scalable, sustainable systems.</li><li>
Use data and experimentation to guide decisions.</li><li>
Communicate openly and collaborate across teams.</li><li>
Support and coach less-experienced engineers.</li><li>
Believe every challenge is an opportunity to simplify and innovate together.</li><li>
Enjoy working with AI to benefit the company, your team and yourself.</li></ul><h2 class="jobSectionHeader"> 
What we are looking for</h2><ul><li>
Hands-on production experience with Scala and functional programming.</li><li>
Ability to design, build, and maintain distributed data systems in a cloud-based environment.</li><li>
Hands-on experience with big data frameworks such as Spark or Databricks.</li><li>
Knowledge of cloud infrastructure (AWS, GCP, or Azure).</li><li>
Judgement to balance scalability, performance, and maintainability.</li><li>
Experience with data modelling and workflow orchestration.</li></ul><h2 class="jobSectionHeader">
Bonus points for</h2><ul><li>
Experience in stream processing frameworks and event-driven architecture.</li><li>
Hands-on experience with Infrastructure as Code (Terraform, CloudFormation).</li><li>
Experience working in containerised environments (Docker, Kubernetes).</li><li>
Interest in AI-driven tooling for engineering workflows.</li><li>
Interest in crypto and blockchain technologies.</li></ul>
How we work:<ul><li>
Hybrid working: The option to work from almost anywhere for up to 90 days per year.</li><li>
Remote Work Budget: $650 budget to set up your home office space.</li></ul>
Learning &amp; Development:<ul><li>
L&amp;D Budget: $1,000 annual Learning &amp; Development budget to use on anything (agreed with your manager) that contributes to your growth and development.</li></ul>
Vacation / Leave:<ul><li>
Holidays: 25 days of annual leave + US Public Holidays.</li><li>
Birthday Leave: An extra day off for your birthday.</li><li>
Enhanced Parental Leave: We provide eligible employees, regardless of gender or whether they become a parent by birth or adoption, 16 weeks fully-paid leave.</li></ul>
Benefits:<ul><li>
Healthcare: Comprehensive medical, dental, and vision coverage through a range of providers (including Tufts, Kaiser, Aetna, UHC, and Blue Shield of CA) with generous premium contributions for you and your dependents.</li><li>
401k: Company match included.</li><li>
Mental Health: Full access to Spill mental health support.</li></ul> 
 
We know Diversity and Inclusion is much deeper than just hiring, but it&rsquo;s important for us to mention it here. We welcome and embrace individuals of all backgrounds and identities at Elliptic, and this is an ongoing priority for us. We know incredible people don&rsquo;t all think in the same way. We want to be challenged every day. We believe our diverse team of individuals underpins this by bringing creative thinking and innovation to Elliptic every day. We are committed to creating a diverse, inclusive and equitable workplace, so we welcome applications from everyone, even if you may not think you fit all of the requirements of our roles. We foster an environment of psychological safety, where everyone feels comfortable to bring their whole self to work. 
 
No recruitment agencies please!
Compensation Range: $165K - $305K</div>

Senior Software Engineer - Data

Google

<div><h3 class="jobSectionHeader">Minimum qualifications:</h3><ul>
<li>Bachelor&rsquo;s degree or equivalent practical experience. 
</li>
<li>5 years of coding experience in one or more of the following languages: C, C++, Java, or Python.</li>
<li>3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture. 
</li>
<li>3 years of experience with developing infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture.</li></ul> 
<h3 class="jobSectionHeader">
Preferred qualifications:</h3><ul>
<li>Master's degree or PhD in computer science or related technical field.</li>
<li>5 years of experience with data structures and algorithms.</li>
<li>Experience in cloud computing, including one or more of the following: public, private cloud, compute, storage, networking, software, platform/infrastructure-as-a-service.</li>
</ul><div><h2 class="jobSectionHeader">About the job</h2>
Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

In this role, you will drive the future of flash storage at Google. You will work on projects, designing and implementing advanced scheduling algorithms for improved user isolation and QoS, micro-optimizing server code for ultra-low latency. You will be responsible for enhancing data integrity through advanced error detection, collaborating with platform teams on design and qualification of new solid-state drive (SSD) hardware, and developing innovative technologies like SmartFTL and write amplification (WAF) reduction techniques.
Google Cloud accelerates every organization&rsquo;s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google&rsquo;s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
 
 
US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits 
 
Learn more about benefits at Google.</div><div><h2 class="jobSectionHeader">
Responsibilities</h2><ul>
<li>Write and test product or system development code.</li>
<li>Participate in, or lead, design reviews with peers and stakeholders to decide amongst available technologies.</li>
<li>Enhance the performance, efficiency, and reliability of Google's core flash storage.</li>
<li>Enable adoption of new SSD technologies to reduce costs and improve capabilities.</li>
<li>Influence future storage hardware designs.</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

Senior Software Engineer, Google Cloud Storage

Qureos

About the company: We build AI hiring agents. They deploy inside the enterprise systems a company already runs, or on the Qureos platform itself for teams who would rather have the whole hiring stack in one place. Either way the agents do the work recruiting teams have always done by hand, from sourcing and screening to interviewing and shortlisting, with speed and consistency no agency or traditional ATS can match. We are a Seed-stage startup backed by Prosus Ventures and COTU Ventures, having raised $5M to accelerate the future of AI-powered hiring. Trusted by more than 1,000 enterprise and public sector organizations, we're scaling rapidly as we build the next generation of AI hiring agents. Operating in a market where every unfilled role and every slow hiring loop costs real money, we are building the future of AI-powered hiring. Our agents let companies run high-volume hiring end to end without ripping out the systems their teams already live in. About the Role As a Forward Deployed Engineer, you will sit at the intersection of engineering, AI, and customer impact. You will work directly with customers to understand how they hire, find the parts of that process worth handing to an agent, and then design, build, and deploy those agents either into the customer's existing enterprise stack or onto the Qureos platform, depending on how they want to run. <ul><li>You will partner closely with customers and Qureos's product and engineering teams to customise agent workflows, improve agent performance, and bring what you learn in live deployments back into the core platform.</li><li>This role is ideal for an engineer who enjoys building production systems, working inside someone else's environment, solving ambiguous problems, and shaping how AI actually gets used in hiring.</li></ul> What You'll Do <ul><li>Embed directly with customers to understand their hiring processes, the systems those processes run on, and where an agent can take over.</li><li>Design, build, and deploy AI hiring agents that source, screen, interview, and move candidates through the funnel.</li><li>Ship those agents into the customer's existing enterprise environment, or onto the Qureos platform for customers who want the all-in-one setup.</li><li>Develop and maintain the infrastructure behind the agents, including APIs, integrations with enterprise ATS and HRIS systems, monitoring, and feedback loops.</li><li>Translate customer requirements into scalable technical solutions and production-ready deployments.</li><li>Collaborate with product and engineering teams to influence roadmap decisions based on what you see in the field.</li><li>Identify patterns across customer deployments and turn one-off integration work into something the platform supports natively.</li><li>Work across engineering, product, and customer teams to ensure successful adoption and long-term impact.</li><li>Operate independently in fast-moving environments where ownership and initiative are highly valued.</li></ul> What You'll Bring <ul><li>3+ years of software engineering experience, preferably with backend, infrastructure, or systems-focused development.</li><li>Strong programming experience in Python (experience with TypeScript/JavaScript is a plus).</li><li>Experience working with cloud platforms such as AWS, GCP, or Azure.</li><li>Ability to design and build reliable production systems, including inside environments you do not control.</li><li>Strong communication skills with the ability to work with both technical and non-technical stakeholders.</li><li>Experience working directly with customers, partners, or cross-functional teams is a plus.</li></ul> Bonus: experience with AI agents, large language models (LLMs), vector databases, prompt engineering, retrieval-augmented generation (RAG), voice agents, or integrating with enterprise ATS and HRIS platforms. Comfortable working in dynamic environments with changing priorities and high ownership. Why Join Us You'll be part of a team building a category-defining AI company in a market that has barely started to change. We move fast, we ship, and we work close to the customer. If you are excited about building AI agents that do real work, deploying them into the systems enterprises actually run, and shaping how hiring gets done, we'd love to hear from you.

Forward Deployed Engineer

<div>Mirage is an AI-native video platform that intelligently orchestrates production and editing through natural language. Our models leverage contextual awareness to execute the same creative decisions a professional editor would &mdash; dramatically improving productivity for experienced teams, while making video creation accessible to anyone. 
 
We&rsquo;re an interdisciplinary team addressing some of the most difficult technical and creative challenges in generative media. As an early member of our team, you&rsquo;ll tackle foundational problems that remain largely unsolved across the industry, driving an outsized impact on the future of creative expression. 
More about us
Product (Captions by Mirage)
Research (Seeing Voices, technical-white-paper)
Updates (Mirage on X / twitter)
TechCrunch, Forbes AI 50, Fast Company (press) 
Our Investors
We&rsquo;re very fortunate to have some the best investors and entrepreneurs backing us, including Index Ventures, Kleiner Perkins, Sequoia Capital, Andreessen Horowitz, General Catalyst, Uncommon Projects, Kevin Systrom, Mike Krieger, Lenny Rachitsky, Antoine Martin, Julie Zhuo, Ben Rubin, Jaren Glover, SVAngel, 20VC, Ludlow Ventures, Chapter One, and more.
Please note that all of our roles will require you to be in-person at our NYC HQ (located in Union Square)
About the Role 
Mirage is seeking an ML Engineer to build and scale the systems powering our video generation models. You&rsquo;ll work on novel modeling approaches, training objectives, scaling strategies, and inference optimization and efficiency to bring cutting-edge models into production.
This role sits at the intersection of research and systems engineering, focusing on making advanced models faster, more efficient, and capable of ultra-low latency, real-time generation.
Responsibilities<ul><li>
Train and optimize large-scale video and multimodal models</li><li>
Improve efficiency across training and inference (memory, latency, cost)</li><li>
Implement techniques such as distillation, quantization, and pruning to aggressively accelerate diffusion and autoregressive generation</li></ul><ul><li>
Build and maintain distributed training systems</li><li>
Optimize GPU utilization, parallelism, and throughput</li><li>
Develop tooling for experimentation, evaluation, and debugging</li></ul><ul><li>
Translate research models into robust, production-ready systems</li><li>
Monitor and improve model performance in real-world usage</li></ul>
What makes you a great fit<ul><li>
BS/MS/PhD in CS, ML, or related field</li><li>
2+ years of professional industry experience</li><li>
Strong experience in deep learning systems and infrastructure</li><li>
Expertise in PyTorch, CUDA, Triton, and distributed training (FSDP, etc.)</li></ul><ul><li>
Experience scaling and optimizing large models under low-latency inference constraints</li><li>
Strong debugging and performance profiling skills</li><li>
Ability to move quickly from prototype to production</li></ul><h3 class="jobSectionHeader">
Benefits:</h3><ul><li>
Comprehensive medical, dental, and vision plans</li><li>
401K with employer match</li><li>
Commuter Benefits</li><li>
Catered lunch multiple days per week</li><li>
Dinner stipend every night if you're working late and want a bite!
</li><li>Grubhub subscription</li><li>
Health &amp; Wellness Perks</li><li>
Multiple team offsites per year with team events every month</li><li>
Generous PTO policy</li></ul>
Captions provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
Please note benefits apply to full time employees only.
Compensation Range: $175K - $275K</div>

Research Engineer, Generative Video

Capital One

<div>Lead Machine Learning Engineer, Card Tech
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:
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 6 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 2 years of experience building, scaling, and optimizing ML systems</li></ul>
Preferred Qualifications:<ul><li>
Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field</li><li>
3+ years of experience building production-ready data pipelines that feed ML models</li><li>
3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow</li><li>
2+ years of experience developing performant, resilient, and maintainable code</li><li>
2+ years of experience with data gathering and preparation for ML models</li><li>
2+ years of people leader experience</li><li>
1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation</li><li>
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform</li><li>
Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance</li><li>
ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents</li><li>
Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion</li></ul>
At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer).
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.
New York, NY: $215,200 - $245,600 for 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>

Lead Machine Learning Engineer, Card Tech

Butterfly Network

<div><h2 class="jobSectionHeader">Company Description</h2>

Butterfly Network, Inc. (NYSE: BFLY) is driving a digital revolution in ultrasound imaging and sensing with its proprietary Ultrasound-on-Chip&trade; semiconductor technology and software solutions. Butterfly first proved its technology in the point-of-care ultrasound market &ndash; commercializing the world's first single-probe, whole-body portable ultrasound device, which is now on its best-selling, third-generation: Butterfly iQ3&trade;. The Company combines its advanced hardware with cloud software and AI, an enterprise workflow solution (Compass AI&trade;) and other offerings to drive adoption of affordable, accessible ultrasound. Butterfly also enables third-party development of imaging AI apps through Butterfly Garden&trade;, its software development kit and AI partnership initiative.

In addition to its medical imaging products, Butterfly Embedded&trade; is the Company's Ultrasound-on-Chip&trade; licensing and co-development program designed to enable a new wave of ultrasound-enabled technologies across non-competitive healthcare markets and beyond. Through Butterfly Embedded&trade;, partners can build and scale novel ultrasound applications powered by Butterfly's proprietary semiconductor chip and software platform. Butterfly's innovations have been recognized by Prix Galien USA, Fierce 50, TIME's Best Inventions and Fast Company's World Changing Ideas, among other achievements.

We're a team of bold thinkers, problem-solvers, and innovators ready to shape the future of medical imaging. Let's build something extraordinary together!
<h2 class="jobSectionHeader">
Job Description</h2>

We're looking for a Staff Site Reliability Engineer to raise the bar for how we observe and operate our production cloud platform. Our cloud platform powers clinical workflows on top of one of the largest ultrasound image repositories in the world. In this role you'll be a hands-on technical contributor who leads by execution.
<h2 class="jobSectionHeader">
What you'll do</h2>
<ul><li>Own observability end to end. Evolve and streamline our metrics, logs, and distributed-tracing strategy. Building telemetry standards that give every team a clear, real-time picture of production health</li>
<li>Drive reliability through SLOs. Establish meaningful service-level objectives with product and engineering teams, and use error budgets to balance velocity against stability.</li>
<li>Lead incident response. Help set the standards for our incident response feedback loop. Manage the on-call rotations for production systems, respond to incidents with calm and rigor, manage blameless postmortems &ndash; then systematically reduce toil.</li>
<li>Engineer for reliability. Operate and improve our Kubernetes/EKS workloads on AWS. Build automation and tooling that removes manual operational work and improves developer productivity.</li>
<li>Be a force multiplier. Mentor engineers on operational excellence, set standards for how services are built to be observable and reliable, and influence architecture decisions across teams.</li>
</ul><h2 class="jobSectionHeader">Qualifications</h2>

Baseline skills/experiences/attributes:
<ul>
<li>8+ years of managing production systems</li>
<li>Deep, hands-on production experience with AWS and Kubernetes</li>
<li>Strong programming/scripting skills and experience building operational automation</li>
<li>Proven ownership of a full stack observability platform (NewRelic/Datadog/etc)</li>
<li>A track record of leading incident response and delivering improvements in reliability</li>
<li>Clear written and verbal communication skills</li>
<li>Strong desire for being a mentor to others</li>
</ul>
Ideally, you also have these skills/experiences/attributes (but it's ok if you don't!):
<ul>
<li>Background operating in a highly regulated or compliance-sensitive environment (e.g., HIPAA, SOC 2, FedRAMP, SaMD, etc).</li>
<li>Background in technical Healthcare Protocols (DICOM, HL7, FHIR) and systems integrations (PACS, VNA, EMR, etc)</li>
</ul><h2 class="jobSectionHeader">Values</h2>

Innovation is what we do. Our values are how we make it happen. Butterflies are and believe in&hellip;
<ul>
<li>Patient-Centric Innovators: Our mission is THE mission.</li>
<li>Empowered to Impact: Every voice matters.</li>
<li>One Team, One Goal: Unity fuels progress.</li>
<li>Growth Champions: We embrace challenges.</li>
<li>Action-Oriented Achievers: We follow through, every time.</li></ul> 

<h2 class="jobSectionHeader">
Location</h2>

Butterfly offers a hybrid work model for most positions, with team members spending two or more days a week in the office. While flexibility is key, we value in-person connections that spark creativity and teamwork. Our offices are designed for collaboration, with comfortable workspaces, stocked kitchens, and opportunities to connect with peers.

This is a hybrid position (2 - 3 days a week in office) and will be based out of our office in New York City, NY. 
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Benefits and Perks</h2>
<ul><li>Comprehensive health insurance, encompassing dental and vision coverage, is provided to all our employees. As a health-tech company, we prioritize the well-being of our teams. We also contribute to Health Savings Account (HSA) accounts for all enrolled employees on an annual basis.</li>
<li>Comprehensive Employee Assistance Program - we provide access to tools and resources to support your emotional health and day-to-day needs.</li>
<li>401k plan and match - we facilitate your retirement goals.</li>
<li>Eligible employees will have the opportunity to participate in Employee Stock Purchase Plan (ESPP)</li>
<li>Unlimited Paid Time Off + 10 Holiday Days a Year - recharge and come back ready to make an impact</li>
<li>Parental Leave - we aim to provide our employees with time to bond with their growing family, along with additional support for primary caregivers to help transition back to work</li>
<li>Competitive salaried compensation - we value our employees and show it</li>
<li>Equity - we want every employee to be a stakeholder</li>
<li>The opportunity to build a revolutionary healthcare product and save millions of lives!</li></ul> 


Compensation

Our estimated salary for this role based in NYC is around $190,000 - $210,000 + bonus + equity + benefits. Actual pay is determined by multiple factors such as skills, qualifications, experience and market demand. 
Candidates must be authorized to work in the United States. Butterfly Network will not provide immigration sponsorship of any kind for this position, including but not limited to H-1B, TN, O-1, L-1, or green card sponsorship (this includes applicants that are in the process of obtaining a greencard), now or in the future.

Butterfly Network does not accept agency resumes.

Butterfly Network is an E-Verify Company.

Butterfly Network is an equal opportunity employer. Regardless of race, traits associated with race, color, ancestry, religion, gender, national origin, sexual orientation, age, citizenship, marital status, disability or Veteran status. All your information will be kept confidential according to EEO guidelines.

Butterfly requires security adherence responsibilities from all employees. These include: adhering to all company security policies and procedures, utilize provided company assets securely, and complete all required security awareness training programs. Safeguarding company data and systems from unauthorized access, modification, or destruction, contributing to the overall security posture of the organization. Immediately reporting any suspected or actual security incidents, including phishing attempts, malware infections, or unauthorized access, following the established incident response procedur 


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Staff , Site Reliability Engineer - Cloud Platform

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