Forward Deployed Engineer
San MateoFull-timePosted 1w ago
About the role
On-site full-time role to deploy AutoScience into customer ML environments, work directly with customers to understand their ML systems, deploy the platform, and ship model improvements into production.
Responsibilities
- Write production code, work inside real ML pipelines, debug distributed systems, reason about machine learning challenges, and collaborate with research and engineering teams to improve the core product.
- Own deployments end-to-end from initial technical conversations to the first model improvement shipped into production.
Qualifications
- Strong software engineering fundamentals and excellent Python skills.
- Experience building, training, evaluating, or deploying machine learning systems.
- Experience working with production cloud infrastructure and containerized workloads.
- Strong debugging skills across software, infrastructure, data, and ML systems.
- Experience owning technically complex projects from an ambiguous starting point through production.
- Good judgment about when to build robust solutions vs. move quickly.
- Ability to communicate deeply technical ideas with researchers, engineers, and technical leaders.
- Eagerness to spend significant time working directly with customers.
- High degree of autonomy and comfort in a fast-moving environment.
Skills
Required:PythonMachine learning systemsCloud infrastructure & containersDebugging across systemsCustomer collaborationProject ownershipTechnical communication
Benefits
- Competitive compensation relative to major LLM frontier lab packages
- Unlimited PTO and flexible working arrangements
- Conference attendance and publication support
Last updated Oct 15, 2026. Interested? Apply on the company site.
About Autoscience
Automate AI Research
Autoscience builds AI systems that train state-of-the-art models for frontier and applied AI labs.
frontier research lab AI models AI R&D enterprise ML AI Observability
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