Job Description

The AGI team at Amazon is seeking a Research Engineer with a strong machine learning background to develop multimodal large-language foundational models. The role involves advancing algorithms and modeling techniques, optimizing training workflows, and leveraging Amazon's data and computing resources to impact customer experiences.

Requirements

Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field
Experience programming with at least one software programming language
PhD or Master's degree in machine learning or equivalent (preferred)
2+ years of full software development life cycle experience (preferred)
Hands-on experience in training Foundational Models/LLMs and low-level optimization of ML training workflows (preferred)

Responsibilities

Responsible for pre and post-training multimodal LLMs
Scale training of models on hyper large GPU and AWS Trainium clusters
Optimize training workflows using distributed training/parallelism techniques
Optimize low-level details of the training stack, including CUDA kernels, communication collectives, network I/O
Utilize, build and extend upon industry leading frameworks (NeMo, Megatron Core, PyTorch, Jax, vLLM, TRT, etc)
Work with other team members to investigate design approaches, prototype new technology, scientific techniques and evaluate technical feasibility
Deliver results independently in a self organizing Agile environment while constantly embracing and adapting new scientific advances

Benefits

Employees at Amazon are often offered comprehensive health benefits—including multiple medical plan options (no pre-existing condition exclusions, 100% covered in-network preventive care), dental and vision plans, a 24/7 medical advice line from day one, expert second-opinion services, and broad mental-health support with several free counseling sessions (including pediatric). Financial wellness typically includes a 401(k) with company match (up to 2%), Restricted Stock Units (equity), FSAs, an emergency savings program, product and partner discounts, and even college-savings and home-purchase programs. Overall, the package is designed to support employees and their families’ health, finances, and day-to-day life.