Machine Learning Systems Research Engineer, Agent Post-training - Enterprise GenAI (LLM)

TL;DR

Machine Learning Systems Research Engineer, Agent Post-training - Enterprise GenAI (LLM): Building and optimizing training and inference systems for enterprise agent models with an accent on post-training algorithms, large-hirify.global GPU infrastructure, and multi-agent rollouts. Focus on designing agent reinforcement learning workflows, profiling distributed systems, and enabling reliable production training for complex enterprise AI applications.

Location: San Francisco, CA; New York, NY. The salary transparency section also lists Seattle as an eligible location.

Salary: $264,800–$331,000 USD base salary, plus potential equity and benefits.

Company

hirify.global develops AI data infrastructure and full-stack technologies that help enterprises and governments build, deploy, and oversee AI applications.

What you will do

• Build, profile, and optimize machine learning training and inference frameworks.
• Post-train internal and community-developed models and establish stable recipes for enterprise engagements.
• Develop next-generation agent training algorithms for multi-agent and multi-tool rollouts.
• Collaborate with ML research teams to accelerate model development and data curation.
• Support large-hirify.global training and integrate state-of-the-art technologies into the ML platform.

Requirements

• 1–3 years of production experience training large language models.
• Experience with post-training methods such as RLHF and RLVR, including PPO or GRPO.
• Experience with multi-node LLM training and inference and operating modern GPU cluster architectures.
• Strong software engineering skills with CUDA, PyTorch, Transformers, FlashAttention, or related tools.
• PhD or master’s degree in computer science or a related field.
• Strong written and verbal communication skills for cross-functional collaboration.

Culture & Benefits

• Health, dental, and vision coverage.
• Retirement benefits, learning and development stipend, and generous paid time off.
• Potential equity compensation for eligible roles, subject to approval.
• Potential commuter stipend depending on eligibility.
• Inclusive equal-opportunity workplace with reasonable accommodations available.