3 days ago
Base Salary
$168k - $262k/yr
Responsibilities
- Lead technical engagements embedded with strategic customers, defining business problems, success metrics, technical roadmaps, milestones, and production delivery.
- Develop customization strategies involving prompting, distillation, supervised fine-tuning, preference optimization, reinforcement learning, continued pre-training, adapters, and domain foundation models.
- Own data strategy, synthetic data generation, evaluation methodology, and generative model benchmarking.
- Design distributed training, RL post-training, inference, and agent interaction systems for large dense and mixture-of-experts models.
- Migrate and optimize training and inference workloads on AWS Trainium, diagnose GPU-parity gaps, and direct kernel-level optimization.
- Lead and mentor FDEs and scientists through workstream planning, design reviews, code reviews, hiring, and technical coaching.
- Create reusable fine-tuning recipes, evaluation frameworks, benchmarking tools, and reference architectures across AWS.
- Influence Amazon Bedrock, Amazon SageMaker AI, and AWS Neuron roadmaps using customer and field evidence.
- Communicate technical trade-offs, risks, and results to customer executives, engineers, and AWS leadership.
- 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 design or architecture for new and existing systems, including design patterns, reliability, and scaling.
- Experience mentoring, serving as a technical lead, or leading an engineering team.
- 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 machine learning 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, including SFT, DPO, RLHF, verifiable-reward RL, 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, AD&D, employee assistance, and mental health support.
- 401(k) matching, paid time off, parental leave, and flexible spending accounts.
- Adoption and surrogacy reimbursement coverage.
- Sign-on payments and restricted stock units may be included in the Amazon package.
- Up to 25% travel is required.
- The listed annual base salary ranges vary by location: $168,100-$261,500.
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.