22 hours ago
Base Salary
$168k - $250k/yr
Responsibilities
- Lead technical engagements embedded with strategic customers and define model customization, optimization, evaluation, and production roadmaps.
- Choose and implement approaches including prompting, distillation, supervised fine-tuning, preference optimization, reinforcement learning, continued pre-training, adapters, and domain foundation models.
- Architect distributed training, RL post-training, inference, evaluation, and agent interaction systems for large-scale dense and mixture-of-experts models.
- Lead migration and optimization of training and inference workloads on AWS Trainium using the AWS Neuron SDK, including performance and accuracy-parity investigations.
- Mentor FDEs and scientists, lead design and code reviews, participate in hiring, and break ambiguous problems into actionable workstreams.
- Create reusable fine-tuning recipes, evaluation frameworks, benchmarking tools, and reference architectures, and influence AWS service roadmaps.
- Own engagement execution, including delivery plans, milestones, risk escalation, scope adjustments, and customer deliverable quality.
- Travel up to 25%.
Requirements
- 5+ years of non-internship professional software development experience.
- 5+ years of programming experience with at least one software programming language.
- 5+ years leading the design or architecture of new and existing systems, including design patterns, reliability, and scaling.
- Experience as a mentor, technical lead, or engineering team lead.
- Hands-on experience training, fine-tuning, or optimizing deep learning models.
- Experience communicating technical concepts to technical and non-technical audiences, including senior leadership.
- Preferred: bachelor's degree in computer science or equivalent.
- Preferred: 2+ years deploying and operating ML models in customer production environments.
- Preferred: experience defining generative-model evaluation strategies and building evaluation frameworks or benchmarks.
- Preferred: experience optimizing model training or inference for latency, throughput, or cost using relevant serving engines, AWS Trainium, AWS services, or custom kernels.
- Preferred: experience leading LLM post-training efforts, including SFT, DPO, RLHF, and verifiable-reward or multi-turn agentic RL.
- Preferred: experience leading large-scale distributed LLM training, including mixture-of-experts models, on multi-node accelerator clusters.
Benefits
- Comprehensive health insurance including medical, dental, vision, prescription, life and AD&D insurance, employee assistance, mental health support, medical advice, flexible spending accounts, and adoption and surrogacy reimbursement.
- 401(k) matching, paid time off, and parental leave.
- Sign-on payments and restricted stock units are included in the Amazon package.
- Work-life flexibility, mentorship, career development resources, and inclusive employee affinity groups and events.
- The role is based in Boston, New York, Arlington, or Seattle and requires up to 25% travel.
Tech Stack
Categories
Forward Deployed
About Amazon
Amazon builds and operates a global e-commerce marketplace, logistics network, and consumer devices, and provides cloud computing via AWS for businesses and developers. The company earns revenue from online retail, third‑party seller services, subscriptions like Prime, advertising, and AWS usage. Founded in 1994 and headquartered in Seattle, it is publicly traded on NASDAQ (AMZN) and serves customers in dozens of countries.