Machine Learning Engineer (AI)

TL;DR

Machine Learning Engineer (AI): Designing and implementing algorithms for agent harness and post-training pipelines with an accent on RL environments and reward models. Focus on developing robust training workflows, optimizing multi-GPU training runs, and improving model capabilities for agentic applications.

Location: Must be based in the US (Hybrid model in Santa Clara, CA; Phoenix, AZ; Folsom, CA; or Hillsboro, OR).

Salary: $170,500–$315,490 USD

Company

hirify.global is a global leader in computing technology, driving innovation in PC platforms, edge hirify.globalligence, and AI-driven hardware solutions.

What you will do

• Build evaluation benchmarks and metrics to assess model performance.
• Develop and iterate on agent harness components, including memory, tools, and skills.
• Maintain and scale post-training pipelines from data ingestion to model deployment.
• Design RL environments and verifiable reward frameworks for reasoning-intensive tasks.
• Debug and optimize training jobs to improve GPU utilization and resolve numerical instability.

Requirements

• BS in CS, EE, Math or related STEM field.
• 5+ years of software development background.
• 2+ years of hands-on experience in machine learning engineering or research.
• Proficiency in Python.
• Deep understanding of LLM architectures, optimization, and training dynamics.
• Must be authorized to work in the United States.

Nice to have

• Masters or PhD degree.
• Experience scaling full post-training pipelines including SFT and RL.
• Ability to own and drive a research agenda independently.
• Strong debug-first mindset for complex ML codebases.

Culture & Benefits

• Competitive total compensation package including stock bonuses.
• Comprehensive health, retirement, and vacation benefits.
• Hybrid work model allowing flexibility between on-site and off-site work.
• Opportunity to work on cutting-edge agentic AI and edge hardware integration.