ML Engineer – AGI/LLM Customization (RSUs, PTO)

Amazon; Boston, Northern (MA, KY); Hybrid; USD 144,000 - 194,000; Full time

Benefits offered by this job

Sign-on payments and RSUs

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon.com Services LLC's AGI Customization team seeks a passionate ML Engineer to drive customization capabilities such as fine-tuning and distillation for multimodal LLMs.

You will partner with Applied Scientists to develop novel training techniques and optimizations, and to scale models on large-scale computing resources in a fast-growing environment.

Join a team that values mentorship, knowledge sharing, and impactful AI products that push the boundaries of Generative AI and AGI research.

Qualifications

• 3+ years of non-internship professional software development experience.
• Experience deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware.
• 3+ years of full software development lifecycle, including coding standards, reviews, and operations experience.
• Knowledge of ML model architecture and inference.
• 3+ years of full software development life cycle across multi-tiered systems using C#, C++, Java, or Perl.

Responsibilities

• Will work with engineers to prototype design approaches and evaluate technical feasibility.
• Process data and scale machine learning models with Applied Scientists.
• Deliver high-quality software in an Agile/Scrum environment.

Skills

Software development

LLM deployment

System design

C/C++/Java

ML frameworks

Education

Bachelor's degree in Computer Science, Engineering, Mathematics, or related field

Bachelor's degree in computer science or equivalent

Tools

PyTorch

JAX

vLLM

TensorRT

TorchXLA

Dynamo

Job description

Amazon.com Services LLC's AGI Customization team seeks a passionate ML Engineer to drive customization capabilities such as fine-tuning and distillation for multimodal LLMs.

You will partner with Applied Scientists to develop novel training techniques and optimizations, and to scale models on large-scale computing resources in a fast-growing environment.

Join a team that values mentorship, knowledge sharing, and impactful AI products that push the boundaries of Generative AI and AGI research.