TL;DR

Research Engineer (Artificial General Intelligence): Develop and optimize multimodal large-language foundational models (LLMs) and generative AI systems with an accent on scaling training workflows on large GPU and AWS Trainium clusters. Focus on designing and implementing distributed training techniques, low-level CUDA kernel optimizations, and building efficient, scalable AI model infrastructure.

Location: Must be based in the United States, specifically Los Angeles County

Salary: $129,300–$223,600 per year

Company

%hirify_global% is a leading technology company focused on advancing artificial intelligence and machine learning through large-scale foundational models and cloud computing.

What you will do

Develop and optimize pre and post-training workflows for multimodal LLMs.
Scale model training on hyper-large GPU and AWS Trainium clusters using distributed training and parallelism.
Optimize low-level training stack components including CUDA kernels, communication collectives, and network I/O.
Utilize and extend industry-leading frameworks such as NeMo, Megatron Core, PyTorch, Jax, and vLLM.
Collaborate with team members to prototype new technologies and evaluate scientific feasibility.
Deliver results independently in an Agile environment while adapting to new scientific advances.

Requirements

Must have a Bachelor's degree or equivalent in Computer Science, Engineering, Mathematics, or related field.
Must be located in the United States, specifically Los Angeles County.
Experience programming in at least one software language.
PhD or Master's degree in machine learning or equivalent preferred.
2+ years of full software development lifecycle experience including coding standards, code reviews, and testing.
Hands-on experience with training foundational models/LLMs and low-level optimization of ML workflows.

Culture & Benefits

Inclusive culture empowering employees to deliver best results.
Comprehensive medical, financial, and other benefits.
Competitive total compensation including equity and sign-on payments.
Support for workplace accommodations and adjustments during hiring and onboarding.