Sr. Research Engineer, Machine Learning, Artificial General Intelligence

Senior Research Engineer, Machine Learning, Artificial General Intelligence Join to apply for the Senior Research Engineer, Machine Learning, Artificial General Intelligence role at Amazon . Description The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Senior Research Engineer (RE) with a strong hands‑on machine learning background, to lead the development of industry‑leading multimodal large‑language foundational models (LLMs). As a Senior RE with the AGI team, you will be responsible for leading the development of novel algorithms and modeling techniques to advance the state of the art. Your work will directly impact our customers and will leverage Amazon’s heterogeneous data sources and large‑scale computing resources to accelerate development with multimodal LLMs and Generative Artificial Intelligence (GenAI). You will have significant influence on our overall strategy by working at the intersection of engineering and applied science to scale pre‑ and post‑training workflows and build efficient models. You will drive the system architecture, and spearhead best practices that enable a quality infrastructure. The ideal candidate is clearly passionate about new opportunities and has a demonstrable track record of success in delivering new features and products. A commitment to teamwork, hustle, and strong communication skills (to both business and technical partners) are absolute requirements. Creating reliable, scalable, and high‑performance products requires exceptional technical expertise, a sound understanding of the fundamentals of Computer Science, and practical experience building large‑scale distributed systems. This person has thrived and succeeded in delivering high‑quality technology products/services in a hyper‑growth environment where priorities shift fast. Key Job 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, and network I/O. Utilize, build, and extend 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. Basic Qualifications 5+ years of non‑internship professional software development experience. 5+ years of programming with at least one programming language. 5+ years of leading design or architecture (design patterns, reliability, and scaling) of new and existing systems. Experience as a mentor, tech lead, or leading an engineering team. 2+ years of expertise in Machine Learning and/or Model Training. Preferred Qualifications Master’s degree in machine learning or equivalent. 5+ years of full software development life cycle experience, including coding standards, code reviews, source control management, build processes, testing, and operations. Hands‑on experience and expertise in training foundational models/LLMs, and/or low‑level optimization of ML training workflows, CUDA kernels, network I/O. About the Team The AGI Foundations team is responsible for building industry‑leading Generative AI foundational models. Seniority Level Mid‑Senior level Employment Type Full‑time Job Function Information Technology, Consulting, and Engineering Industries Software Development Company Amazon.com Services LLC Job ID A3145951 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 working safely and cooperatively with other employees, supervisors, and staff; adhering to standards of excellence despite stressful conditions; communicating effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and following 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 for more information. 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 U.S. geographic markets. The base pay for this position ranges from $151,300/year in our lowest geographic market up to $261,500/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. Depending 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 This position will remain posted until filled. Applicants should apply via our internal or external career site. Referrals increase your chances of interviewing at Amazon by 2x. #J-18808-Ljbffr