Staff ML Engineer: Build Production-Grade AI Systems

Primer.ai; Washington (District of Columbia); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Medical, dental, vision

Wellness Days

Paid parental leave

Remote work stipend

Monthly internet allowance

401(k)

Job summary

Primer is seeking a Staff Machine Learning Engineer to own AI-driven products from prototype to production. You will work across LLMs, agentic systems, retrieval, embeddings, and evaluation to deliver reliable, scalable solutions.

Collaborate with product managers and engineers to shape the technical roadmap, design distributed systems, and deploy low-latency inference while maintaining high quality and safety standards.

Qualifications

• BS, MS, or PhD in computer science or related field or equivalent practical experience.
• 6+ years building production backend software with ML-driven functionality.
• Strong data structures & algorithms judgment to translate user needs.
• Hands-on depth with LLMs and agentic systems and ML toolkit incl. PyTorch.
• Fluency authoring production APIs in Python (Rust a plus).
• High agency and bias to action in fast-moving problems and teaching others.

Responsibilities

• Set technical and product direction across LLM, agentic, and NLP systems.
• Design and build distributed, agentic systems at scale.
• Turn real-world data into trustworthy signals for reasoning.
• Take models from checkpoint to production with low-latency inference.
• Build evals and data flywheels to guide work.
• Partner with cross-functional teams to shape the roadmap.
• Raise engineering bar with better patterns and practices.

Skills

Production backend

LLMs & agents

Python APIs

Data structures

Distributed systems

PyTorch

Leadership

Education

BS/MS/PhD in computer science

Tools

PyTorch

Rust

Job description

Primer is seeking a Staff Machine Learning Engineer to own AI-driven products from prototype to production. You will work across LLMs, agentic systems, retrieval, embeddings, and evaluation to deliver reliable, scalable solutions.

Collaborate with product managers and engineers to shape the technical roadmap, design distributed systems, and deploy low-latency inference while maintaining high quality and safety standards.