Software Development Engineer (ml), Agi Customization, Agi Customization

Amazon Amazon · Big Tech · Boston, MA · Software Development

ML Engineer role focused on developing customization capabilities like fine-tuning and distillation for LLMs, advancing LLM training techniques, and optimizing multimodal LLMs and Generative AI solutions. Requires experience deploying LLMs in production and knowledge of ML frameworks.

What you'd actually do

  1. leading the development of novel LLM training techniques and optimizations to advance the state of LLMs
  2. collaborate closely with Applied Scientists and leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate development of multimodal Large Language Models and Generative Artificial Intelligence solutions
  3. Will work with other team engineers to investigate design approaches, prototype new technology and evaluate technical feasibility
  4. Work closely with Applied scientists to process data, scale machine learning models while optimizing
  5. Will work in an Agile/Scrum environment to deliver high quality software

Skills

Required

  • 3+ years of non-internship professional software development experience
  • Experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware
  • 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • Knowledge of machine learning model architecture and inference
  • 3+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience
  • Knowledge of ML frameworks including JAX, PyTorch, vLLM, SGLang, Dynamo, TorchXLA, and TensorRT

Nice to have

  • 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
  • Bachelor's degree in computer science or equivalent

What the JD emphasized

  • delivering new features and products
  • absolute requirements
  • exceptional technical expertise
  • sound understanding of the fundamentals of Computer Science and Machine Learning
  • thrived and succeeded in delivering high quality technology products/services in a hyper-growth environment
  • Experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware
  • Knowledge of machine learning model architecture and inference

Other signals

  • LLM training techniques
  • optimizations
  • multimodal Large Language Models
  • Generative Artificial Intelligence solutions
  • fine tuning
  • distillation