machine learning engineer, model customization, generative ai innovation center Jobs in Seattle

machine learning engineer, model customization, generative ai innovation center

senior machine learning engineer Jobs in Seattle

senior machine learning engineer

senior manager, ai marketing initiatives - bellevue Jobs in Seattle

senior manager, ai marketing initiatives - bellevue

senior/principal machine learning engineer Jobs in Seattle

senior/principal machine learning engineer

software development engineer - ai/ml, aws neuron, multimodal inference Jobs in Seattle

software development engineer - ai/ml, aws neuron, multimodal inference

senior principal machine learning engineer

Workday

<div><div>Your work days are brighter here.</div><div></div><div>
We&rsquo;re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we&rsquo;re shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you&rsquo;ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We&rsquo;re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you&rsquo;ll do meaningful work with Workmates who&rsquo;ve got your back. In return, we&rsquo;ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you&rsquo;ve found a match in Workday, and we hope to be a match for you too.</div><div></div><div>
About the Team</div>
Agent Factory is where Workday&rsquo;s next chapter gets built. We&rsquo;re forming small, senior, cross-functional AI teams that bring together product leaders, machine learning engineers, and full-stack builders to create intelligent agents used by millions of people every day. This is production-grade AI&mdash;deeply embedded into Workday&rsquo;s platform&mdash;not research experiments or maintenance work. Teams own problems end to end, collaborate tightly across disciplines, and use the right tools to solve real customer challenges at global scale. You&rsquo;ll work at the intersection of AI, platform architecture, and human workflows, with the autonomy to shape how agents reason, act, and scale responsibly. High trust, high expectations, and real impact. Engineering, but brighter.<div></div><div>
About the Role</div><div></div><div>
As a Senior/Principal Machine Learning Engineer in Agent Factory, you&rsquo;ll design and build the core ML systems behind Workday&rsquo;s next generation of AI agents. Working within a small, senior, cross-functional pod, you&rsquo;ll own how models, agent logic, and orchestration layers come together in production&mdash;across the full lifecycle from problem framing and data strategy to deployment, monitoring, and continuous improvement. You&rsquo;ll implement and evolve frameworks for LLM-powered agents, including RAG pipelines, workflow orchestration, evaluation, and feedback loops, ensuring solutions are scalable, observable, and enterprise-ready. This role sits at the intersection of ML and platform engineering: partnering closely with software engineers, product managers, and data scientists to integrate agents deeply into the Workday stack. You&rsquo;ll stay hands-on with emerging techniques in agentic architectures while applying strong engineering judgment to turn them into systems that are reliable, explainable, and built to operate at global scale.</div><div></div><div>
About You</div><div></div><div>
Principal Machine Learning Engineer - Basic Qualifications</div><ul><li><div>
10+ years experience as a member of a data science, machine learning engineering, or other relevant software development team building applied machine learning products at scale, including taking products through applied research, design, implementation, production, and production-based evaluation</div></li><li><div>
4+ years of professional experience in machine learning and deep learning frameworks &amp; toolkits such as Pytorch, TensorFlow</div></li><li><div>
6+ years of professional experience in building services to host machine learning models in production at scale</div></li><li><div>
3+ years of demonstrated experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases</div></li><li><div>
6+ years of proven experience with cloud computing platforms (e.g. AWS, GCP, etc.)</div></li><li><div>
Proven track record of successfully leading, mentoring, and/or managing ML Engineering teams, taking ownership of development lifecycle and sprint planning; fostering a culture of collaboration, transparency, innovation, and continuous improvement</div></li><li><div>
Bachelor&rsquo;s (Master&rsquo;s or PhD preferred) degree in engineering, computer science, physics, math or equivalent</div></li></ul><div></div><div>
Senior Machine Learning Engineer - Basic Qualifications</div><ul><li><div>
7+ years experience as a member of a data science, machine learning engineering, or other relevant software development team building applied machine learning products at scale, including taking products through applied research, design, implementation, production, and production-based evaluation</div></li><li><div>
3+ years of professional experience in machine learning and deep learning frameworks &amp; toolkits such as Pytorch, TensorFlow</div></li><li><div>
4+ years of professional experience in building services to host machine learning models in production at scale</div></li><li><div>
2+ years of demonstrated experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases</div></li><li><div>
4+ years of proven experience with cloud computing platforms (e.g. AWS, GCP, etc.)</div></li><li><div>
Proven track record of successfully leading, mentoring, and/or managing ML Engineering teams, taking ownership of development lifecycle and sprint planning; fostering a culture of collaboration, transparency, innovation, and continuous improvement</div></li><li><div>
Bachelor&rsquo;s (Master&rsquo;s or PhD preferred) degree in engineering, computer science, physics, math or equivalent</div></li></ul><div></div><div>
Other Qualifications:</div><ul><li><div>
Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks to drive innovation</div></li><li><div>
Deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms, and natural language processing for information retrieval and/or recommendation system use cases</div></li><li><div>
Professional experience in independently solving ambiguous, open-ended problems and technically leading teams</div></li><li><div>
Excellent interpersonal and communication skills, with the ability to build strong relationships across teams and stakeholders</div></li><li><div>
Proven track record of successfully leading, mentoring, and/or managing ML Engineering teams, taking ownership of development lifecycle and sprint planning; fostering a culture of collaboration, transparency, innovation, and continuous improvement.</div></li></ul><div><br>
Workday Pay Transparency Statement</div><div></div><div>
The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate&rsquo;s compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday&rsquo;s comprehensive benefits, please <div>click here</div>.</div><div></div>
Primary Location: USA.WA.Seattle<div></div>
Primary Location Base Pay Range: $215,000 USD - $322,600 USD<div></div>
Additional US Location(s) Base Pay Range: $194,600 USD - $345,600 USD<div><br>
Our Approach to Flexible Work</div><div><br>
With Flex Work, we&rsquo;re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote &quot;home office&quot; roles also have the opportunity to come together in our offices for important moments that matter.</div><div></div><div>
Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records.</div><div></div><div>
Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans.</div><div></div><div>
Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!</div><div>
At Workday, we value our candidates&rsquo; privacy and data security. Workday will never ask candidates to apply to jobs through websites that are not Workday Careers.</div><div></div><div><br>
Please be aware of sites that may ask for you to input your data in connection with a job posting that appears to be from Workday but is not.</div><div></div><div><br>
In addition, Workday will never ask candidates to pay a recruiting fee, or pay for consulting or coaching services, in order to apply for a job at Workday.</div></div>

Senior/Principal Machine Learning Engineer

Paradox

<div><p><b>Your work days are brighter here.
</b></p><p></p><p>We&rsquo;re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we&rsquo;re shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you&rsquo;ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We&rsquo;re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you&rsquo;ll do meaningful work with Workmates who&rsquo;ve got your back. In return, we&rsquo;ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you&rsquo;ve found a match in Workday, and we hope to be a match for you too.
</p><p></p><p><b>About the Team
</b></p>Agent Factory is where Workday&rsquo;s next chapter gets built. We&rsquo;re forming small, senior, cross-functional AI teams that bring together product leaders, machine learning engineers, and full-stack builders to create intelligent agents used by millions of people every day. This is production-grade AI&mdash;deeply embedded into Workday&rsquo;s platform&mdash;not research experiments or maintenance work. Teams own problems end to end, collaborate tightly across disciplines, and use the right tools to solve real customer challenges at global scale. You&rsquo;ll work at the intersection of AI, platform architecture, and human workflows, with the autonomy to shape how agents reason, act, and scale responsibly. High trust, high expectations, and real impact. Engineering, but brighter.
<p></p><p><b>About the Role
</b></p><p></p><p>As a Full Stack Software Engineer in Agent Factory, you&rsquo;ll help build the user-facing and platform experiences that bring Workday&rsquo;s AI agents to life. Working within a small, cross-functional pod, you&rsquo;ll design and ship full stack solutions&mdash;from intuitive front-end experiences to resilient backend services that integrate AI-driven capabilities deeply into HR and Finance workflows. This role is about turning powerful technology into products people actually use: scalable, reliable systems that simplify complex business processes for customers around the world. You&rsquo;ll collaborate closely with machine learning engineers, product managers, and platform teams, owning features end to end and seeing your work run in production. If you enjoy building real products, solving meaningful problems, and working with people who care about quality and craft, you&rsquo;ll feel right at home here.
</p><p></p><p>Your responsibilities:
</p><ul><li><p>Build and deliver full stack features that power AI agents embedded in HR and Financial workflows
</p></li><li><p>Own services and experiences from development through production&mdash;you build it, you run it
</p></li><li><p>Collaborate in an iterative, team-first environment that values strong engineering practices and continuous learning
</p></li><li><p>Share knowledge, mentor teammates, and help raise the technical bar across the pod
</p></li></ul><p></p><p><b>About You
</b></p><p></p><p><b>Senior Software Development Engineer - Basic Qualifications:
</b></p><ul><li><p>8+ years of experience in software engineering
</p></li><li><p>5+ years experience with a web development framework (Python preferred: Flask, Django, or FastAPI)
</p></li><li><p>5+ years with a Relational DB (PostgreSQL preferred)
</p></li></ul><p></p><p><b>Software Development Engineer III - Basic Qualifications:
</b></p><div><div><div><div><div><div><div><div><div><ul><li><p>5+ years of experience in software engineering
</p></li><li><p>2+ years experience with a web development framework (Python preferred: Flask, Django, or FastAPI)
</p></li><li><p>2+ years of experience with React and Typescript for Front End / Full stack development
</p></li><li><p>2+ years with a Relational DB (PostgreSQL preferred)
</p></li></ul></div></div></div></div></div></div></div></div></div><p></p><p><b>Other Qualifications:
</b></p><ul><li><p>Bachelor's degree in a computer related field or equivalent work experience
</p></li><li><p>Experience building and operating SaaS products in cloud environments (AWS preferred)
</p></li><li><p>Familiarity with the tradeoffs and architecture of modern distributed systems
</p></li><li><p>Knowledge of software development best practices (DevOps, CI/CD, automated testing, observability)
</p></li><li><p>Hands-on experience with containerization technologies (Docker, Kubernetes)
</p></li><li><p>Familiarity with Elasticsearch
</p></li><li><p>Exposure to additional programming languages like Java (backend) and TypeScript (frontend/fullstack) is a plus
</p></li><li><p>Proven success working within fast-paced, agile environments and cross-functional teams
</p></li><li><p>Strong communication skills, with the ability to collaborate with both technical and non-technical partners
</p></li><li><p>Comfortable working with ambiguity and translating complex problems into clear, thoughtful solutions
</p></li><li><p>Committed to fostering an inclusive, team-oriented environment and contributing to a culture of continuous improvement<br>
</p></li></ul><p><br>
<b>Workday Pay Transparency Statement
</b></p><p></p><p>The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate&rsquo;s compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday&rsquo;s comprehensive benefits, please click here .
</p><p></p>Primary Location: USA.WA.Seattle
<p></p>Primary Location Base Pay Range: $161,300 USD - $241,900 USD
<p></p>Additional US Location(s) Base Pay Range: $145,900 USD - $259,200 USD<br>
<p><br>
<br>
<b>Our Approach to Flexible Work<br>
</b><br>
</p><p>With Flex Work, we&rsquo;re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply <b>spend at least half (50%) of our time each quarter in the office or in the field </b>with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote &quot;home office&quot; roles also have the opportunity to come together in our offices for important moments that matter.
</p><p></p><p>Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records.
</p><p></p><p>Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans.
</p><p></p><p><b>Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!
</b></p><p>At Workday, we value our candidates&rsquo; privacy and data security. Workday will never ask candidates to apply to jobs through websites that are not Workday Careers.<br>
</p><p></p><p>Please be aware of sites that may ask for you to input your data in connection with a job posting that appears to be from Workday but is not.<br>
</p><p></p><p>In addition, Workday will never ask candidates to pay a recruiting fee, or pay for consulting or coaching services, in order to apply for a job at Workday.</p></div>

Software Development Engineer III / Senior Software Development Engineer - Full Stack

Amazon.com

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
As a Senior Data Engineer on the PXT (People Experience and Technology) Central Science team at Amazon, you will be part of the Data team that builds the foundational data infrastructure and analytics tools for PXTCS. We create secure, scalable solutions that enable teams across PXTCS to access and analyze data effectively while maintaining data integrity. In this role, you will design, build, and maintain scalable data pipelines and infrastructure that power our people analytics capabilities. You will collaborate with data scientists, business intelligence engineers, and HR business partners to transform complex HR data into actionable insights that drive Amazon's people strategy. Your technical expertise will help us make data-driven decisions that enhance the employee experience across Amazon's global workforce<br>
<br>
Key job responsibilities<br>
<ul><li>Design, develop, and maintain efficient ETL processes and data pipelines to collect, process, and integrate data from multiple HR systems and sources</li><li>Build and optimize data models that support advanced analytics, reporting, and machine learning applications</li><li>Implement data quality controls and monitoring systems to ensure accuracy and reliability of people data</li><li>Partner with data scientists to productionize machine learning models that solve complex workforce challenges</li><li>Collaborate with stakeholders to understand business requirements and translate them into technical solutions</li><li>Mentor junior engineers and contribute to establishing best practices for data engineering</li><li>Continuously improve data architecture to enhance performance, scalability, and security</li></ul><br>
About the team<br>
The People eXperience and Technology Central Science (PXTCS) team uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. PXTCS is an interdisciplinary team that combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal.</div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>5+ years of data engineering experience</li><li>Experience with data modeling, warehousing and building ETL pipelines</li><li>Experience mentoring team members on best practices</li><li>Experience working with Data &amp; AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage</li><li>Bachelor's degree or above in computer science, engineering, mathematics or equivalent, or PhD</li><li>Experience with SQL and Python scripting</li><li>Experience with AWS services including S3, Redshift, EMR and RDS</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience with big data technologies such as: Hadoop, Hive, Spark, EMR</li><li>Experience operating large data warehouses</li><li>Knowledge of professional software engineering &amp; best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence</li><li>Master's degree in Computer Science or related technical field</li><li>Knowledge of HR data structures and people analytics use cases</li><li>Experience with workflow orchestration tools (Airflow, Step Functions)</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
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.<br>
<br>
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.<br>
<br>
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.<br>
<br>
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $139,100/year in our lowest geographic market up to $240,500/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.</div>

Data Engineer, People Experience and Technology Central Science

Amazon Web Services

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
The Annapurna Labs team at Amazon Web Services (AWS) builds AWS Neuron, the software development kit used to accelerate deep learning and GenAI workloads on Amazon&rsquo;s custom machine learning accelerators, Inferentia and Trainium.<br>
<br>
The AWS Neuron SDK, developed by the Annapurna Labs team at AWS, is the backbone for accelerating deep learning and GenAI workloads on Amazon's Inferentia and Trainium ML accelerators. This comprehensive toolkit includes an ML compiler, runtime, and application framework that seamlessly integrates with popular ML frameworks like PyTorch and JAX enabling unparalleled ML inference and training performance.<br>
<br>
The Inference Enablement and Acceleration team is at the forefront of running a wide range of models and supporting novel architecture alongside maximizing their performance for AWS's custom ML accelerators. Working across the stack from PyTorch till the hardware-software boundary, our engineers build systematic infrastructure, innovate new methods and create high-performance kernels for ML functions, ensuring every compute unit is fine tuned for optimal performance for our customers' demanding workloads. We combine deep hardware knowledge with ML expertise to push the boundaries of what's possible in AI acceleration.<br>
<br>
As part of the broader Neuron organization, our team works across multiple technology layers - from frameworks and kernels and collaborate with compiler to runtime and collectives. We not only optimize current performance but also contribute to future architecture designs, working closely with customers to enable their models and ensure optimal performance. This role offers a unique opportunity to work at the intersection of machine learning, high-performance computing, and distributed architectures, where you'll help shape the future of AI acceleration technology<br>
<br>
You will architect and implement business critical features, and mentor a brilliant team of experienced engineers. We operate in spaces that are very large, yet our teams remain small and agile. There is no blueprint. We're inventing. We're experimenting. It is a very unique learning culture. The team works closely with customers on their model enablement, providing direct support and optimization expertise to ensure their machine learning workloads achieve optimal performance on AWS ML accelerators. The team collaborates with open source ecosystems to provide seamless integration and bring peak performance at scale for customers and developers.<br>
<br>
This role is responsible for development, enablement and performance tuning of a wide variety of LLM model families, including massive scale large language models like the Llama family, DeepSeek and beyond. The Inference Enablement and Acceleration team works side by side with compiler engineers and runtime engineers to create, build and tune distributed inference solutions with Trainium and Inferentia. Experience optimizing inference performance for both latency and throughput on such large models across the stack from system level optimizations through to Pytorch or JAX is a must have.<br>
<br>
You can learn more about Neuron<br>
https://awsdocs-neuron.readthedocs-hosted.com/en/latest/neuron-guide/neuron-cc/index.html<br>
https://aws.amazon.com/machine-learning/neuron/<br>
https://github.com/aws/aws-neuron-sdk<br>
https://www.amazon.science/how-silicon-innovation-became-the-secret-sauce-behind-awss-success<br>
<br>
Key job responsibilities<br>
This role will help lead the efforts in building distributed inference support for Pytorch in the Neuron SDK. This role will tune these models to ensure highest performance and maximize the efficiency of them running on the customer AWS Trainium and Inferentia silicon and servers. Strong software development using Python, System level programming and ML knowledge are both critical to this role. Our engineers collaborate across compiler, runtime, framework, and hardware teams to optimize machine learning workloads for our global customer base. Working at the intersection of software, hardware, and machine learning systems, you'll bring expertise in low-level optimization, system architecture, and ML model acceleration. In this role, you will:<br>
<br>
<ul><li>Design, develop, and optimize machine learning models and frameworks for deployment on custom ML hardware accelerators.</li><li>Participate in all stages of the ML system development lifecycle including distributed computing based architecture design, implementation, performance profiling, hardware-specific optimizations, testing and production deployment.</li><li>Build infrastructure to systematically analyze and onboard multiple models with diverse architecture.</li><li>Design and implement high-performance kernels and features for ML operations, leveraging the Neuron architecture and programming models</li><li>Analyze and optimize system-level performance across multiple generations of Neuron hardware</li><li>Conduct detailed performance analysis using profiling tools to identify and resolve bottlenecks</li><li>Implement optimizations such as fusion, sharding, tiling, and scheduling</li><li>Conduct comprehensive testing, including unit and end-to-end model testing with continuous deployment and releases through pipelines.</li><li>Work directly with customers to enable and optimize their ML models on AWS accelerators</li><li>Collaborate across teams to develop innovative optimization techniques</li></ul><br>
A day in the life<br>
You will collaborate with a cross-functional team of applied scientists, system engineers, and product managers to deliver state-of-the-art inference capabilities for Generative AI applications. Your work will involve debugging performance issues, optimizing memory usage, and shaping the future of Neuron's inference stack across Amazon and the Open Source Community. As you design and code solutions to help our team drive efficiencies in software architecture, you&rsquo;ll create metrics, implement automation and other improvements, and resolve the root cause of software defects.<br>
<br>
You will also build high-impact solutions to deliver to our large customer base and participate in design discussions, code review, and communicate with internal and external stakeholders. You will work cross-functionally to help drive business decisions with your technical input. You will work in a startup-like development environment, where you&rsquo;re always working on the most important initiative.<br>
<br>
About the team<br>
The Inference Enablement and Acceleration team fosters a builder&rsquo;s culture where experimentation is encouraged, and impact is measurable. We emphasize collaboration, technical ownership, and continuous learning. Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we&rsquo;re building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future. Join us to solve some of the most interesting and impactful infrastructure challenges in AI/ML today.</div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>3+ years of non-internship professional software development experience</li><li>Bachelor's degree or equivalent in Computer Science</li><li>3+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience</li><li>Fundamentals of Machine learning and LLMs, their architecture, training and inference lifecycles along with work experience on optimizations for improving the model execution.</li><li>Software development experience in C++, Python (experience in at least one language is required).</li><li>Strong understanding of system performance, memory management, and parallel computing principles.</li><li>Proficiency in debugging, profiling, and implementing best software engineering practices in large-scale systems.</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Familiarity with PyTorch, JIT compilation, and AOT tracing.</li><li>Familiarity with CUDA kernels or equivalent ML or low-level kernels.</li><li>Candidates with performant kernel development such as CUTLASS, FlashInfer etc., would be well suited.</li><li>Familiar with syntax and tile-level semantics similar to Triton.</li><li>Experience with online/offline inference serving with vLLM, SGLang, TensorRT or similar platforms in production environments.</li><li>Deep understanding of computer architecture, operation systems level software and working knowledge of parallel computing.</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
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.<br>
<br>
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.<br>
<br>
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129,300/year in our lowest geographic market up to $223,600/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.</div>

Software Development Engineer - AI/ML, AWS Neuron, Multimodal Inference

Foundational AI Research Scientist - FAIR

Uber

<div><b>About the Role</b>
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The Reserve product is a maturing product, most of the low hanging fruit&quot; initiatives to improve the experience to consistently deliver high reliability have been delivered. Currently, our focus is in building smart levers to maintain reliability while driving efficiency, improving our unit economics and growing adoption and retention.
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Some of the key projects involve major changes in Pricing, Matching and Dispatch that involve transitioning from heuristic based decision making to building machine learning models to make key decisions in real time, as well as important changes to Driver and Rider experience, including discoverability and awareness generation levers, and finally piloting new use cases that leverage the Reserve Tech as a platform to unlock new vectors of growth.
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<b>What You Will Do</b>
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<ul><li>Deploy a wide variety of methodologies, including causal inference techniques, experiments, funnel analyses, ML modeling and Optimization algorithms to solve real world business and customer problems.
</li><li>Work together with Product, Operations, and Engineering partners to design a roadmap of features and initiatives as well as the long-term team strategy
</li><li>Present findings to technical and non-technical audiences.
</li></ul>- Basic Qualifications -
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<ul><li>Ph.D., M.S. or Bachelor's degree in Statistics, Mathematics, Computer Science, Machine Learning, Operations Research, or other quantitative fields.
</li><li>2+ years of industry experience as an Applied or Data Scientist or equivalent (not required with Ph.D.).
</li><li>Proficiency in programming languages (Python, Java, Scala) and ML frameworks (TensorFlow, PyTorch, Scikit-Learn), underpinned by a solid grasp of MLOps practices, including design documentation, testing, and source code management with Git.
</li><li>Good understanding of experimental design and analysis (e.g., A/B and market-level experiments), causal inference.
</li><li>Good business and product sense: delight in shaping vague questions into well-defined analyses and success metrics that drive business decisions.
</li></ul>- Preferred Qualifications -
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<ul><li>Ability to drive clarity on the best modeling or analytic solution for a business objective
</li><li>Experience in building statistical, optimization, and machine learning models for a range of applications.
</li><li>Expertise in causal inference, A/B testing designs, multivariate testing, and other advanced analytical methods.
</li><li>Experience in designing highly scalable, resilient systems for customer-facing applications and familiarity with optimization techniques.
</li><li>Propose, design, and analyze large scale online experiments and interpret the results to draw detailed and actionable conclusions.
</li>Collaborate with cross-functional teams across disciplines such as product, engineering, operations, and marketing to drive system development end-to-end from ideation to productionization<br>
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</li></ul><br>
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For Seattle, WA-based roles: The base salary range for this role is USD$155,000 per year - USD$172,000 per year. You will be eligible to participate in Uber's bonus program, and may be offered an equity award &amp; other types of comp. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/benefits.</div>

Scientist II - Reservations

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
About Sponsored Products and Brands<br>
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The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising.
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Sponsored Products Search Relevance&rsquo;s (SPSR) team&rsquo;s mission is to help shoppers easily find and discover the most useful and relevant sponsored products, while improving advertisers&rsquo; ability to find the right shoppers in the right context for their sponsored products. We develop capabilities to understand shoppers&rsquo; queries, shopping missions, and products&rsquo; attributes so that we can identify ASINs that are contextually relevant to the shopper. We make CX/UX improvements so that shoppers can easily perceive why products are relevant to them and efficiently navigate Amazon&rsquo;s vast product selection.<br>
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We are seeking an Applied Science Manager with a strong background in ML and Gen AI solutions. The ideal candidate shall have experience managing both scientists and engineers and will be passionate about applying these technologies to the advertising domain.<br>
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Curious about our advertising solutions? Discover more about Sponsored Products and Sponsored Brands to see how we&rsquo;re helping businesses grow on Amazon.com and beyond!<br>
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Key job responsibilities<br>
As an Applied Science Manager, you will:<br>
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<ul><li>Directly manage and lead a cross-functional team of Applied Scientists, Machine Learning Engineers, and Software Development Engineers.</li><li>Develop science and engineering roadmaps for SPB Search Relevance with ML and Gen AI solutions, run annual planning, and foster cross-team collaboration on model development and integration to advertising applications.</li><li>Hire and develop top talent, provide technical and career development guidance to scientists and engineers within and across the organization.</li><li>Stay informed about recent scientific publications, industrial research trends, and system designs that are pertinent to the SPB advertising business and bring those insights with the team.</li></ul><br>
About the team<br>
Sponsored Products Search Relevance&rsquo;s (SPSR) team&rsquo;s mission is to help shoppers easily find and discover the most useful and relevant sponsored products, while improving advertisers&rsquo; ability to find the right shoppers in the right context for their sponsored products. We develop capabilities to understand shoppers&rsquo; queries, shopping missions, and products&rsquo; attributes so that we can identify ASINs that are contextually relevant to the shopper. We make CX/UX improvements so that shoppers can easily perceive why products are relevant to them and efficiently navigate Amazon&rsquo;s vast product selection.</div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>4+ years of applied research experience</li><li>3+ years of scientists or machine learning engineers management experience</li><li>3+ years of building machine learning models for business application experience</li><li>PhD, or Master's degree and 6+ years of applied research experience</li><li>Knowledge of ML, NLP, Information Retrieval and Analytics</li><li>Experience programming in Java, C++, Python or related language</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers</li><li>PhD, or a Master's degree and experience with generative deep learning models applicable to the creation of synthetic humans like CNNs, GANs, VAEs and NF</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
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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.<br>
<br>
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $165,500/year in our lowest geographic market up to $286,000/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.</div>

Applied Science Manager, Sponsored Products and Brands

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