AmazonSenior Applied Scientist, Annapurna ML
AI in this role
The AWS Neuron Science Core Algorithm team is looking for talented Applied Scientists to push the frontier of hardware-aware machine learning for Trainium and Inferentia, the AWS Machine Learning accelerators. In this rare role at the intersection of LLM modeling, large-scale training systems, and hardware/datatype co-design, you own model and algorithm decisions jointly with AWS custom silicon. You will own solutions end-to-end from research through production, publish at top venues, and work alongside distinguished engineers and scientists in a strategic growth area for AWS.
We actively work on these areas:
- Low-precision training and inference: MXFP8, MXFP4, and sub-4-bit training and inference recipes, stochastic rounding, and Trn4 datatype exploration.
- Trn-friendly architectures: model architectures that exploit hardware strengths without sacrificing quality.
- System-aware optimizers & efficient distributed systems: efficient optimizers and distributed systems that give the best accuracy, co-designed with the hardware.
- Foundation-model pre-training accuracy: end-to-end validation across model scales, catching training divergence early, and equivalence-checking tooling.
- GenAI for systems: RL post-training for NKI kernel generation, mitigating reward-hacking and accelerating under low precision on Trn.
Key job responsibilities
- Own scientific problems end-to-end - from research and experimentation through production impact - applying rigorous evaluation to complex, ill-defined problems at large scale.
- Develop production-quality code in PyTorch or JAX and integrate scientific components into large-scale training and inference systems with operational excellence and efficient resource usage.
- Partner with foundation-model, engineering, and hardware-architecture teams so your findings directly inform what gets built into Trainium and shipped in the product stack.
- Mentor fellow scientists and interns, give constructive peer reviews, and help shape team goals, priorities, and the technical roadmap.
- Author and publish research at top peer-reviewed venues (ICLR, NeurIPS, ICML, MLSys) and engage the broader scientific community.
Basic qualifications
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- 3+ years of building machine learning models for business application experience
- Experience with neural deep learning methods and machine learning
Preferred qualifications
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, CA, Cupertino - 192,200.00 - 260,000.00 USD annually
How we rate this
Senior Applied Scientist, Annapurna ML at Amazon rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- What's a project where you used PyTorch hands-on?
- Walk me through how you've used TensorFlow in your day-to-day work.
- What are the limits of scikit-learn that you've run into, and how did you work around them?
- What's a project where you used Jax hands-on?
- How would you decide a model or AI system is ready to ship?
Adapt your resume
- List these exact terms on your resume: PyTorch, TensorFlow, scikit-learn, and Jax. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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