Sr Applied Scientist, ML Codesign, Edge AI Platform

Define the joint optimization of model compression and silicon architecture for Amazons next generation of edge and cloud inference accelerators. Your work will set the technical targets that propagate across the model compiler runtime and silicon stack.

We are hiring a Sr. Applied Scientist to be the technical leader who closes the loop between compression science and silicon design. Todays generation ships advanced quantization and large-model distillation in production running multi-billion parameter language models at inference economics typical of much larger systems. Future generations target significantly larger models at the edge and in the cloud. You will be a senior architect of the next-generation accelerator and of the compression algorithms it executes natively. Few roles in the industry let one technical leader influence the model the compiler the runtime and the silicon without organizational friction. This is one of them.

You have spent the last several years thinking about why hardware decisions and accuracy decisions live in different teams and you want to be the person who owns both. You have published at MLSys ISCA MICRO NeurIPS or ICML on quantization pruning or hardware-aware training and you want your next paper to ship in a chip rather than in a benchmark suite. You want a vertical stackmodel compression compiler runtime operating system siliconwhere the same engineering organization owns every layer and a sr. architect can move all of them.

Key job responsibilities
Define the hardware-aware compression roadmap for next-generation accelerators working backward from accuracy targets on standard language and reasoning benchmarks including Massive Multitask Language Understanding (MMLU) GSM8K HumanEval and Instruction Following Evaluation (IFEval).

Own the joint optimization of compression algorithms (post-training quantization quantization-aware training knowledge distillation structured pruning) with the underlying hardware.

Represent applied science in silicon architecture reviews and influence decisions across the memory and compute subsystems of the accelerator.

Set the science roadmap for the compression techniques the next architecture must support; validate that compression algorithms achieve target accuracy on the benchmarks our products are evaluated against.

Mentor a team of senior and mid-level applied scientists working on compression and hardware-aware training.

Serve as a single-threaded technical leader for the codesign agenda accountable to senior leadership review.

About the team
Amazons Devices and Services organization has shipped multiple generations of first-party silicon for consumer devices. The differentiating intellectual property across this portfolio is a custom machine learning processor co-designed with the compression algorithms it runs.

This role sits at the intersection of three teams. The Applied Science team produces compressed model checkpoints. The Silicon Engineering team designs the Application-Specific Integrated Circuits (ASICs). The Compiler and Runtime team lowers compressed models to silicon. You will be the Sr. architect who closes the loop across all three.

- 3 years of building machine learning models for business application experience
- PhD or Masters degree and 6 years of applied research experience
- Experience programming in Java C Python or related language
- Experience with neural deep learning methods and machine learning

- 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 Companys 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 for more information. If the country/region youre applying in isnt 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 CA Sunnyvale - 192200.00 - 260000.00 USD annually