ML & Agentic Systems Engineer
New
S
SourcegraphSoftware Engineering
While we hire almost anywhere in the world, we have a preference for someone to reside in the following locations for this role: Europe or North America., Must overlap with EST for at least 20 hours/week.Full-TimeStaff
SalaryZone 2: $176,000 USD, Zone 3: $132,000 USD, Zone 4: $88,000 USD
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Job Details
- Required Skills
- DockerGraphQLMachine LearningTypeScriptGoPostgres
Requirements
- Expertise as a staff engineer with a proven track record in production machine learning, evaluation, and agent systems.
- Experience owning a production model lifecycle from dataset construction through evaluation, rollout, and monitoring.
- Fluency in designing and maintaining reliable, observable, and cost-bounded multi-step agentic systems.
- Strong judgment in creating evaluation harnesses, baselines, and release criteria.
- Strong software engineering fundamentals with the ability to ship production-grade services.
- Proficiency with Go, TypeScript, GraphQL, Postgres, and Docker, or the eagerness to learn them quickly.
- Experience mentoring engineers and acting as a force multiplier for a product-minded team.
- Ability to work autonomously on ambiguous, high-risk technical problems.
- Strong communication skills for customer interaction and cross-functional collaboration.
- Ability to operate effectively in an async-first, remote environment.
Responsibilities
- Design and harden multi-step, tool-using agent loops to turn research into reliable, observable products at enterprise scale.
- Develop pragmatic evaluation strategies, including metrics, smoke tests, and error taxonomies to measure model changes.
- Manage production model lifecycles, including model selection, upgrading, and fine-tuning.
- Improve retrieval and context engineering to ensure model accuracy and verifiability.
- Optimize for cost and latency by profiling, distilling, caching, and right-sizing models.
- Collaborate with customers and internal stakeholders to frame problems and define product roadmaps.
- Mentor teammates and raise the team's overall agent engineering literacy through pairing and design reviews.
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