Machine Learning Engineer (AI)

TL;DR

Machine Learning Engineer (AI): Designing and maintaining large-scale distributed training systems for LLMs and multi-modal models with an accent on performance optimization, efficiency, and throughput. Focus on building Ray-based infrastructure, developing scalable pipelines for data preprocessing, and orchestrating frontier LLMs with complex tool use.

Location: Hybrid and On-Site in Cambridge, MA or San Francisco, CA, USA

Salary: $116,000–$170,000 USD per year

Company

hirify.global is pioneering a new age of boundless discovery by building the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science.

What you will do

• Design and maintain Ray-based distributed training infrastructure for LLMs and multi-modal models.
• Optimize performance for large-scale model training including SFT, MoE, and long-context scaling.
• Orchestrate frontier and open-source LLMs along with complex compute-intensive tool use.
• Develop scalable pipelines for data preprocessing and experiment orchestration.
• Implement system-level performance benchmarks and debugging utilities.

Requirements

• Proven experience with distributed ML training frameworks (Megatron-LM, TorchTitan, DeepSpeed, Ray).
• Strong software engineering skills (Python).
• Understanding of large-scale model training techniques.
• Experience with cloud or HPC environments.

Nice to have

• Prior work with scientific datasets or domain-specific modeling.
• Contributions to open-source ML frameworks.
• C++ kernel contributions.

Culture & Benefits

• Competitive base salary and generous early equity.
• Commitment to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
• Opportunity to work on scientific superintelligence to solve humankind's greatest challenges in human health, climate, and sustainability.