ai learning content producer Jobs in Seattle

ai learning content producer

applied scientist, ml compiler Jobs in Seattle

applied scientist, ml compiler

data engineer, people experience and technology central science Jobs in Seattle

data engineer, people experience and technology central science

director of product, personalization & growth Jobs in Seattle

director of product, personalization & growth

foundational ai research scientist - fair Jobs in Seattle

foundational ai research scientist - fair

machine learning engineer model customization generative ai innovation center

Amazon Web Services

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
The Generative AI Innovation Center at AWS empowers customers to harness state of the art AI technologies for transformative business opportunities. Our multidisciplinary team of strategists, scientists, engineers, and architects collaborates with customers across industries to fine-tune and deploy customized generative AI applications at scale. Additionally, we work closely with foundational model providers to optimize AI models for Amazon Silicon, enhancing performance and efficiency.
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As an SDE on our team, you will drive the development of custom Large Language Models (LLMs) across languages, domains, and modalities. You will be responsible for fine-tuning state-of-the-art LLMs for diverse use cases while optimizing models for high-performance deployment on AWS&rsquo;s custom AI accelerators. This role offers an opportunity to innovate at the forefront of AI, tackling end-to-end LLM training pipelines at massive scale and delivering next-generation AI solutions for top AWS clients.<br>
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Key job responsibilities<br>
<ul><li>Large-Scale Training Pipelines: Design and implement distributed training pipelines for LLMs using tools such as Fully Sharded Data Parallel (FSDP) and DeepSpeed, ensuring scalability and efficiency
</li><li>LLM Customization &amp; Fine-Tuning: Adapt LLMs for new languages, domains, and vision applications through continued pre-training, fine-tuning, and Reinforcement Learning with Human Feedback (RLHF)
</li><li>Model Optimization on AWS Silicon: Optimize AI models for deployment on AWS Inferentia and Trainium, leveraging the AWS Neuron SDK and developing custom kernels for enhanced performance
</li><li>Customer Collaboration: Interact with enterprise customers and foundational model providers to understand their business and technical challenges, co-developing tailored generative AI solutions<br>
</li></ul><br>
<br>
About the team<br>
ABOUT AWS:<br>
<br>
Diverse Experiences
<br>
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn&rsquo;t followed a traditional path, or includes alternative experiences, don&rsquo;t let it stop you from applying.
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Why AWS
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Amazon Web Services (AWS) is the world&rsquo;s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating &mdash; that&rsquo;s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.<br>
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Work/Life Balance
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We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there&rsquo;s nothing we can&rsquo;t achieve in the cloud.<br>
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Inclusive Team Culture
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AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.<br>
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Mentorship and Career Growth<br>
We&rsquo;re continuously raising our performance bar as we strive to become Earth&rsquo;s Best Employer. That&rsquo;s why you&rsquo;ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.<br>
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AWS Global Services<br>
AWS Global Services includes experts from across AWS who help our customers design, build, operate, and secure their cloud environments. Customers innovate with AWS Professional Services, upskill with AWS Training and Certification, optimize with AWS Support and Managed Services, and meet objectives with AWS Security Assurance Services. Our expertise and emerging technologies include AWS Partners, AWS Sovereign Cloud, AWS International Product, and the Generative AI Innovation Center. You&rsquo;ll join a diverse team of technical experts in dozens of countries who help customers achieve more with the AWS cloud.</div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>3+ years of non-internship professional software development experience</li><li>2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience</li><li>Bachelor's degree in computer science or equivalent</li><li>Hands-on experience with deep learning and/or machine learning methods (e.g. for training, fine tuning, and inference)</li><li>Hands-on experience with generative AI technology</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience</li><li>1+ years of programming with at least one software programming language experience</li><li>1+ years of experience hands-on experience with developing, deploying, or optimizing machine learning models using a recognized ML library or framework</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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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>
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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>
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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>

Machine Learning Engineer, Model Customization, Generative AI Innovation Center

Amazon.com

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
The Sponsored Products and Brands (SPB) team at Amazon Ads is transforming advertising through generative AI technologies. We help millions of customers discover products and engage with brands across Amazon.com and beyond. Our team combines human creativity with artificial intelligence to reinvent the entire advertising lifecycle&mdash;from ad creation and optimization to performance analysis and customer insights.<br>
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We develop responsible AI technologies that balance advertiser needs, enhance shopping experiences, and strengthen the marketplace. Our team values innovation and tackles complex challenges that push the boundaries of what's possible with AI.<br>
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Join us in shaping the future of advertising.<br>
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Key job responsibilities<br>
This role will redesign how ads create personalized, relevant shopping experiences with customer value at the forefront. Key responsibilities include:<br>
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<ul><li>Design and develop solutions using GenAI, deep learning, multi-objective optimization and/or reinforcement learning to transform ad retrieval, auctions, whole-page relevance, and shopping experiences.</li><li>Partner with scientists, engineers, and product managers to build scalable, production-ready science solutions.</li><li>Apply industry advances in GenAI, Large Language Models (LLMs), and related fields to create innovative prototypes and concepts.</li><li>Improve the team's scientific and technical capabilities by implementing algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling.</li><li>Mentor junior scientists and engineers to build a high-performing, collaborative team.</li></ul><br>
A day in the life<br>
As an Applied Scientist on the Sponsored Products and Brands Off-Search team, you will contribute to the development in Generative AI (GenAI) and Large Language Models (LLMs) to revolutionize our advertising flow, backend optimization, and frontend shopping experiences. This is a rare opportunity to redefine how ads are retrieved, allocated, and/or experienced&mdash;elevating them into personalized, contextually aware, and inspiring components of the customer journey. You will have the opportunity to fundamentally transform areas such as ad retrieval, ad allocation, whole-page relevance, and differentiated recommendations through the lens of GenAI. By building novel generative models grounded in both Amazon&rsquo;s rich data and the world&rsquo;s collective knowledge, your work will shape how customers engage with ads, discover products, and make purchasing decisions. If you are passionate about applying frontier AI to real-world problems with massive scale and impact, this is your opportunity to define the next chapter of advertising science.<br>
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About the team<br>
The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across various surfaces beyond Search on Amazon&mdash;such as product detail pages, the homepage, and store-in-store pages&mdash;to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences, scales across diverse page types, remains relevant to seasonal and event-driven moments, and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options. To execute this vision, we work in close partnership with Amazon Stores stakeholders to lead the expansion and growth of advertising across Amazon-owned and -operated pages beyond Search. We operate full stack&mdash;from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences&mdash;all designed to deliver meaningful value.</div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><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>Experience programming in Java, C++, Python or related language</li><li>Strong foundation in GenAI, large language models, machine learning, deep learning, probabilistic modeling, and/or optimization.</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Demonstrated expertise in Generative AI technologies, including foundation models, LLMs, and model customization for specific business applications</li><li>Hands-on experience building ads ranking, retrieval, recommendation, or personalization systems that operate at web scale</li><li>Technical proficiency in advanced AI approaches such as multi-modal modeling, few-shot learning, retrieval-augmented generation (RAG), or reinforcement learning from human feedback (RLHF)</li><li>Track record of designing and implementing online experimentation frameworks, including A/B testing methodologies and performance metrics for advertising or e-commerce</li><li>Proven ability to translate complex technical concepts into clear explanations for diverse audiences, from engineers to executives</li><li>Deep knowledge of computational advertising fundamentals, including auction mechanisms, advertising economics, and advertiser success metrics</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>
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 $150,400/year in our lowest geographic market up to $260,000/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>

Senior Applied Scientist, Sponsored Products and Brands, Off-Search

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
About Sponsored Products and Brands<br>
<br>
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>
<br>
<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>
<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 $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

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

<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>
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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>
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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>
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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>
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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>
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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

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><p>
This role is one of the AWS Communications teams' most senior leaders, telling stories about how AWS is developing advanced generative and agentic AI technology and how customers and partners around the world are using it to innovate.<br>
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Key job responsibilities<br>
This role is responsible for working with senior technology leaders, researchers, and distinguished engineers to discover stories about the advanced AI technology being developed inside AWS and translate that innovation into inspiring stories for customers around the world.
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This role will work across earned, owned, and social media to translate complex technical topics into easy to understand stories and campaigns that reflect AWS's advanced innovation across generative and agentic AI.<br>
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This role will be responsible for working with reporters and colleagues in the US, and around the world, to make sure AWS's story is heard by customers of all sizes, from startups to enterpreises to governments.
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This role will own the development of strategic programs and the execution of large, strategic events that get worldwide press attention. It will be responsible for the development and execution of the entire communications plan, working with colleagues across marketing, sales, engineering, customer support, and more, working up to CEO and Senior Vice President-level within the company.<br>
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A day in the life<br>
No day is the same. One day this role will be focused on launching a new service, the next developing a plan for a large-scale, global event, the next diving deep into reporting to understand how we can better improve our storytelling in the future. A candidate that embraces diversity in their role, constantly strives to learn, and able to quickly pivot their work priorities will thrive in the dynamic environment this team brings.<br>
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About the team<br>
The team has a high performance culture that is based on continual learning, strong teamwork, and delivering high quality results. The team lives the Amazonian mantra of &quot;work hard, have fun, make history&quot; an constantly strives to innovate new ways to communicate about innovation to customers.</p><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>10+ years of recent professional communications or public relations experience</li><li>Bachelor's degree</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience in professional communications or public relations</li><li>Experience working in B2B Tech PR, preferably with experience working on generative AI and agentic AI programs.</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>
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>
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Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $135,700/year in our lowest geographic market up to $224,300/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>

AI Communications, AWS Communications

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