Staff Machine Learning Engineer

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 exists to make the world a safer place. We do this by providing trusted decision-ready AI to the world's most critical organizations. Our software enables leaders, operators, and analysts to better understand the changing world around us in real time and make informed decisions when the stakes are high. Primer has offices in San Francisco, Pasadena, CA and Arlington, VA. For more information, please visit https://primer.ai/

Primer exists to make the world a safer place. We build trusted, decision-ready AI for the organizations that can least afford to be wrong: the leaders, operators, and analysts making high-stakes calls about a world that changes faster than anyone can read it. We have offices in San Francisco, Pasadena, CA, and Arlington, VA. Learn more at primer.ai.

The world produces more information every day than any team can read. We build the AI that turns it into a decision you can trust: fast and grounded enough to stake real consequences on.

As a Staff Machine Learning Engineer, you'll own AI-driven products end to end, from the prototype that proves an idea works to the production system the mission depends on. You work fluently across the modern stack: large language models, agentic systems, retrieval, embeddings, fine-tuned models, and the evaluation harnesses that catch them when they drift. You can move fast on an open-ended problem and then harden the result into something reliable at scale, drawing on real distributed-systems experience. You're energized by what frontier models and agents make newly possible. You reach for them reflexively, including to multiply your own output, and you raise the level of everyone around you as you go.

Your technical range matters as much as your judgment about how the pieces fit together. The best work here is designed as part of the whole system, not bolted on beside it, and the engineers with the most impact bring product managers and teammates along with them rather than around them. You'll partner with product, engineering, and other technical leaders on the hardest version of the problem: putting real AI in the hands of people the moment a decision can't wait.

Role and Responsibilities - How You Will Make an Impact

• Set both technical and product direction, making the strategic bets across our LLM, agentic, and NLP systems while shaping how we design AI-driven experiences and set expectations with users.
• Design and build the distributed, agentic systems behind our products at company-wide scale: tool-using conversational agents, multi-turn context, retrieval-grounded reasoning, and the orchestration that ties them together.
• Turn massive, messy, real-world data into the trustworthy signal agents' reason over: entity recognition and linking, relation extraction, summarization, semantic search, and knowledge-graph generation.
• Take models from checkpoint to production: package, deploy, and operate low-latency, high-concurrency inference (Triton, vLLM, GPU-backed serving) that stays fast and reliable under real load.
• Build the evals and labeled-data flywheels that steer the work rather than gate it, turning "it feels better" into proof you can act on.
• Partner with and influence cross-functional teams to shape the technical roadmap, and drive issues to root cause when quality or operations are on the line.
• Raise the engineering bar with better patterns, better practices, and a standard other engineers want to match.

Relevant Skills And Experience

• BS, MS, or PhD in computer science, a related field, or equivalent practical experience.
• 6+ years building production backend software, with a track record of shipping and operating ML-driven functionality.
• Mastery of data structures and algorithms, and the judgment to translate user needs into practical solutions.
• Hands-on depth with LLMs and agentic systems (prompt and context engineering, tool use, retrieval and RAG) and the broader ML toolkit such as PyTorch, plus experience defining evals to measure and improve quality.
• Fluency authoring production APIs in Python (Rust a plus).
• High agency and a bias to action in ambiguous, fast-moving problems, plus the curiosity, generosity, and love of teaching that lifts a whole team.

Bonus Points

• Experience with knowledge graphs, information retrieval at scale, or LLM fine-tuning and post-training.
• A pull toward high-stakes, real-world problems where the work actually ships and someone depends on the answer.

Primer works closely with the U.S. defense and intelligence establishment. Any offer of employment is conditioned on an applicant or employee being able to meet any applicable government contract requirements. The company may rescind any offer of employment to an applicant or terminate an employee if the applicant or employee is unable to perform the functions of the position in compliance with applicable government contracts or if an applicant or employee makes a false attestation of compliance.

What We Offer

We are a series D funded company with investors from Addition, USIT, Lux Capital, Amplify Partners, Addition Capital, Bloomberg Beta, and others. We are intentional around building a diverse and inclusive team of subject matter experts to better advocate for the needs of our users.

We care a lot about our work and about the well being of our team. We encourage everyone to work at a sustainable pace and have a flexible vacation policy for team members to utilize, Wellness Days and 100% paid leave for parents of growing families.

We offer competitive compensation and comprehensive benefits. This includes full medical, dental, and vision coverage, fertility benefits through Carrot, mental health coverage on demand with Headspace Care+, Gympass+ Membership via Wellhub, One Medical Membership, 401(k), remote work stipends, and monthly internet allowance.

Primer is proud to be an Equal Employment Opportunity and Aff… we do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. Please see the United States Department of Labor's EEO poster and EEO poster supplement for additional information.

If you need assistance or accommodation due to a disability, you may contact us at [e-mail].

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.