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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Forward Deployed Engineer - **Company:** GOODFIRE, LLC - **Location:** San Francisco, CA, United States - **Salary:** $200,000.0 - $325,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Python (Programming Language), Performance Tuning, Tensorflow, Azure Machine Learning, Software Engineering, Large Language Models, Production Code, Api Management - **Published:** September 5, 2026 - **Apply:** https://startup.jobs/forward-deployed-engineer-goodfire-8129769 ## About the Role * Strong software engineering skills with production experience in Python and modern ML frameworks (PyTorch, JAX). * Ability to work across research and engineering boundaries - you can understand a new technique and figure out how to ship it. * Scrappiness, willingness to persist in ambiguity, ability to learn quickly, and a generalist "can-do" mindset. * Strong communication skills - you can explain technical tradeoffs clearly to both engineers and non-technical stakeholders., * Technical degree or equivalent professional experience within AI, ML, or a related field. * Experience in a forward-deployed, solutions, or customer-facing engineering role. Former technical founders encouraged to apply. * Track record of excellence in a high-growth startup or frontier AI lab. * Experience with large language models, including fine-tuning, evaluation frameworks, or agent development. * Familiarity with interpretability, mechanistic interpretability, or model internals (sparse autoencoders, feature steering, etc.). ## Description We're looking for a Forward Deployed Engineer to be the technical backbone of our customer engagements, the person who takes our interpretability platform and makes it work inside a partner's environment, end-to-end. This role demands strong engineering capability, the ability to learn new domains fast, the creativity to design solutions under real-world constraints, and the comfort to operate directly alongside customer engineering and research teams. This is a hands-on, high-ownership role where you will be forward-deployed with our most strategic partners: writing production code, building integrations, running pilots, and owning technical delivery day-to-day. This role turns frontier research into deployed reality. You will typically be working with deeply technical partners - Heads of AI, research teams, ML platform teams - across Life Sciences, Robotics and Vision, Language and Reasoning models, or new verticals, helping them integrate our platform into their model training stack., * Own technical delivery for partner engagements: build production-grade integrations of Goodfire's platform into customer environments - from API integrations and custom pipelines to internal tooling and evaluation workflows * Run pilots that prove value fast: design and execute creative, short-timeline pilots that demonstrate the platform's impact, often in parallel with or ahead of longer-term solution scoping * Embed with partner engineering teams: serve as the day-to-day technical point of contact, going deep in their codebase, understanding their infrastructure, and building trust through competence * Compound learnings across engagements: bring field insights back to the platform and research teams, identify repeatable patterns, and build shared tooling and playbooks that scale the Field Team * Bridge research and production: take novel interpretability methods from the Foundational Team and figure out how to make them work reliably in a partner's stack - this means being comfortable reading papers, prototyping new techniques, and hardening them for production use ## Related Videos - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [From APIs to MCP: Enterprise Governance, Registry, and Controls](https://www.wearedevelopers.com/videos/100336-from-apis-to-mcp-enterprise-governance-registry-and-controls) - [Designing the Future of Human<>Agent Collaboration](https://www.wearedevelopers.com/videos/1447-designing-the-future-of-human-agent-collaboration) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [How We Built a Machine Learning-Based Recommendation System (And Survived to Tell the Tale)](https://www.wearedevelopers.com/videos/752-how-we-built-a-machine-learning-based-recommendation-system-and-survived-to-tell-the-tale) - [Building the Next Generation of Software](https://www.wearedevelopers.com/videos/100186-building-the-next-generation-of-software) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Dev Digest 132 - Binging WADFlix?](https://www.wearedevelopers.com/magazine/473-dev-digest-132-binging-wadflix) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere)