Machine Learning Engineer

Annapurna Labs designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time agoeven yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world. AWS Neuron is the complete software stack for the AWS Trainium (Trn1/Trn2) and Inferentia (Inf1/Inf2) our cloud-scale Machine Learning accelerators. This role is for a Machine Learning Engineer on one of our AWS Neuron teams:

ML Distributed Training

The ML Distributed Training team works side by side with chip architects, compiler engineers and runtime engineers to create, build and tune distributed training solutions with Trainium instances. Experience with training these large models using Python is a must. FSDP (Fully-Sharded Data Parallel), Deepspeed, Nemo and other distributed training libraries are central to this and extending all of this for the Neuron based system is key.

ML Frameworks

ML Frameworks partners with compiler, runtime, and research experts to make AWS Trainium and Inferentia feel native inside the tools builders already lovePyTorch, JAX, and the rapidly evolving vLLM ecosystem. By weaving Neuron SDK deep into these frameworks, optimizing operators, and crafting targeted extensions, we unlock every teraflop of Annapurna's AI chips for both training and lightning-fast inference. Beyond kernels, we shape next-generation serving by upstreaming new features and driving scalable deployments with vLLM, Triton, and TensorRTturning breakthrough ideas into production-ready AI for millions of customers.

ML Inference

The ML Inference team collaborates closely with hardware designers, software optimization experts, and systems engineers to develop and optimize high-performance inference solutions for Inferentia chips. Proficiency in deploying and optimizing ML models for inference using frameworks like TensorFlow, PyTorch, and ONNX is essential. The team focuses on techniques such as quantization, pruning, and model compression to enhance inference speed and efficiency. Adapting and extending popular inference libraries and tools for Neuron-based systems is a key aspect of their work.

Key job responsibilities include improving PyTorch and JAX for distributed training on Trainium chips, optimizing ML models for efficient inference on Inferentia processors, and collaborating with compiler and runtime teams to maximize hardware performance. You'll also develop and integrate new features in ML frameworks to support AWS AI services.

We seek candidates with strong programming skills, eagerness to learn complex systems, and basic ML knowledge. This role offers growth opportunities in ML infrastructure, bridging the gap between frameworks, distributed systems, and hardware acceleration.

Basic qualifications include a Bachelors or Masters degree between December 2022 and September 2025, working knowledge of C++ and Python, experience with ML frameworks, particularly PyTorch, Jax, and/or vLLM, and understanding of parallel computing concepts and CUDA programming.

Preferred qualifications include open source contributions to ML frameworks or tools, experience optimizing ML workloads for performance, direct experience with PyTorch internals or CUDA optimization, and hands-on experience with LLM infrastructure tools (e.g., vLLM, TensorRT).

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. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $99,500/year in our lowest geographic market up to $200,000/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.