Staff ML Engineer: Build Production-Grade AI Systems

Primer.ai

Washington (District of Columbia)

Vor Ort

USD 180.000 - 240.000

Vollzeit

14 Tage+

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Benefits dieser Stelle

Medical, dental, vision
Wellness Days
Paid parental leave
Remote work stipend
Monthly internet allowance
401(k)

Zusammenfassung

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.

Qualifikationen

  • 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.

Aufgaben

  • 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.

Kenntnisse

Production backend
LLMs & agents
Python APIs
Data structures
Distributed systems
PyTorch
Leadership

Ausbildung

BS/MS/PhD in computer science

Tools

PyTorch
Rust

Jobbeschreibung

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.

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