Docker helps developers bring their ideas to life by conquering the complexity of app development.
ML Engineer
Location
California
Posted
4 days ago
Salary
$138.5K - $225.5K / year
Seniority
Senior
Job Description
ML Engineer
Docker, Inc
• Design, train, evaluate, and ship ML systems that power governance and security capabilities, starting with problems like prompt injection detection, behavioral anomaly detection, trust scoring, and policy recommendations. • Build the supporting infrastructure: data pipelines, feature stores, model serving, evaluation harnesses, and the feedback loops that make iteration fast. • Make pragmatic build-vs-buy calls. Use frontier models, off-the-shelf tooling, and managed services to move quickly; invest in custom systems where they create durable advantage. • Set technical direction for the team's ML work. Own the architecture, evaluation methodology, model lifecycle, and the bar for shipping. • Help recruit, mentor, and shape the team as it grows. • This role may require participation in a 24/7 on-call rotation for the Agentic Platform; carry genuine pager responsibility for the services you build and operate
Job Requirements
- 5+ years of deep applied ML/AI expertise with a track record of shipping production systems. Experience in fraud, abuse, safety, security, or trust domains, where adversarial dynamics, imbalanced data, and high-stakes decisions is valuable.
- 4+ years of professional, hands-on, full-time software engineering experience in backend, infrastructure, or platform engineering.
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
- You've built and owned the systems around ML models, i.e. data pipelines, serving, evaluation, monitoring etc. and have shipped customer-facing products end to end.
- You use modern AI tools fluently in your day-to-day work and have a sharp instinct for when frontier models can replace traditional ML, when they can't, and when to combine the two.
- Experience with LLM-based systems in production - evaluation, prompt engineering, fine-tuning, retrieval, guardrails, agent frameworks.
- Familiarity with the agent / MCP ecosystem.
- You're energized by an early-stage effort where the roadmap is being written as the work happens, and you make crisp decisions with incomplete information.
- Collaborative and low-ego. You work well across teams, write clearly, and bring others along.
Benefits
- Freedom & flexibility; fit your work around your life
- Designated quarterly Whaleness Days plus end of year Whaleness break
- Home office setup; we want you comfortable while you work
- 16 weeks of paid Parental leave (after 6 months of employment)
- Technology stipend equivalent to $100 USD net/month
- PTO plan that encourages you to take time to do the things you enjoy
- Training stipend for conferences, courses and classes
- Equity; we are a growing start-up and want all employees to have a share in the success of the company
- Docker Swag
- Medical benefits, retirement and holidays vary by country
- Remote-first culture, with offices in Seattle and Paris
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