TL;DR

Machine Learning Engineer (AI): Develop and optimize large-scale training pipelines and custom Large Language Models (LLMs) for diverse applications, focusing on generative AI and model deployment on AWS custom silicon. Focus on designing scalable distributed training, fine-tuning LLMs with advanced techniques, and optimizing AI models for high-performance cloud deployment.

Location: Remote

Salary: $129,300–$223,600 per year

Company

%hirify_global% is part of Amazon Web Services, a leading global cloud platform innovating in AI and cloud computing.

What you will do

Design and implement distributed training pipelines for large language models using tools like FSDP and DeepSpeed.
Fine-tune and customize LLMs for new languages, domains, and vision applications including RLHF.
Optimize AI models for deployment on AWS Inferentia and Trainium using AWS Neuron SDK and custom kernels.
Collaborate with enterprise customers and foundational model providers to co-develop tailored generative AI solutions.

Requirements

Bachelor's degree in Computer Science, Engineering, Mathematics, or related field
2+ years of professional software development experience
Experience in design or architecture of scalable systems
Hands-on experience with deep learning, machine learning, and generative AI technologies
English proficiency at least B2 level

Nice to have

Experience with ML system training and deployment at large scale
Familiarity with ML libraries or frameworks
Full software development lifecycle experience including code reviews and testing

Culture & Benefits

Flexible work-life balance and remote work culture
Inclusive and diverse team environment with employee-led affinity groups
Mentorship and continuous career growth opportunities
Comprehensive compensation including equity and benefits