ML Engineer, Agentic Systems

🔥 0 minutes ago

🏈 North America – Remote

💵 $88k - $176k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 0%

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Sourcegraph

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2013

🤖 Artificial Intelligence

☁️ SaaS

🏢 Enterprise

💰 $150M Series D on 2021-07

Artificial Intelligence • SaaS • Enterprise

Sourcegraph is a company providing code intelligence solutions designed to help developers efficiently navigate and understand complex codebases. It offers tools like code search and context-aware AI to help developers write, fix, and refactor code with ease. Sourcegraph improves productivity by automating tasks such as unit testing and documentation, allowing developers to focus more on development. Its AI coding assistant, Cody, enhances coding efficiency by providing code completions and insights directly within developers' IDEs. Sourcegraph is trusted by large development teams for simplifying codebase management and increasing engineering productivity.

📋 Description

• Set the Code Understanding team's direction for models, evaluations, and agentic systems • Design and harden multi-step, tool-using agent loops for reliable, observable, affordable enterprise-scale products • Determine when and how to use evaluations, smoke tests, metrics, and qualitative review • Select, upgrade, fine-tune, and train models where appropriate • Improve retrieval, ranking, context windows, and citations for code-grounded answers • Optimize model cost and latency through profiling, distillation, caching, and right-sizing • Own meaningful agentic product slices end-to-end from problem framing through rollout and measurement • Establish evaluations, dashboards, and guardrails for responsible model and prompt changes • Mentor and up-level teammates in agent engineering • Engage with customers and translate feedback into requirements, scopes, and milestones • Contribute across the codebase and influence technical direction beyond the immediate team • Participate in the on-call support rotation • Drive roadmap direction and measurable improvements in answer quality, cost, latency, and agentic capabilities

🎯 Requirements

• Staff engineer and technical leader with production machine learning, evaluation, and agent systems expertise • Personally owned a production model lifecycle from dataset construction through evaluation, production rollout, and monitoring • Trained or fine-tuned at least one model • Experience designing reliable, observable, and cost-bounded multi-step agentic systems • Strong evaluation judgment, including representative datasets, baselines, error taxonomies, and release criteria • Ability to make quality, latency, and cost tradeoffs using model selection, prompting, retrieval, caching, distillation, and fine-tuning • Ability to operate autonomously on ambiguous, high-technical-risk problems • Strong software engineering skills and ability to ship production services • Comfortable across Go, TypeScript, GraphQL, Postgres, and Docker, or clearly able and eager to learn them • Fluent with agentic coding tools and able to understand and own every line they submit • Comfortable in an async-first, multi-service, fast-paced remote environment • Ability to mentor engineers through pairing, design reviews, and code reviews • Customer- and product-driven approach • Working hours must overlap with EST for at least 20 hours per week

🏖️ Benefits

• Meaningful equity • Competitive cash compensation • Generous perks and benefits • Open and transparent compensation philosophy • Pay bands designed for competitive and equitable compensation • Globally distributed remote work arrangement • Flexible location options in almost any part of the world • Equal opportunity workplace