Docker, Inc

Docker, Inc

ML Engineer

Palo Alto, CA · Staff+ · Full-time

Sponsorship not specifiedDetected 36 days ago
DockerMachine LearningData EngineeringLLMs

About the role

  • We're hiring a ML Engineer as one of the founding engineers on Intelligence Org.
  • This is a hands-on builder role with staff-level scope: you'll shape technical direction, ship the first versions of intelligence capabilities into customer hands, and grow the foundations (data, evaluation, infrastructure) the team will rely on as it scales.

Responsibilities

  • 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.
  • carry genuine pager responsibility for the services you build and operate
  • 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.
  • We are committed to building a team that represents a variety of backgrounds, perspectives, and skills.
  • From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout.
  • The Intelligence team builds intelligence-driven product capabilities that make software and agent execution on Docker safer, more effective, more trustworthy, and more efficient.

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
  • Experience with LLM-based systems in production - evaluation, prompt engineering, fine-tuning, retrieval, guardrails, agent frameworks.
  • You work well across teams, write clearly, and bring others along.
  • we want you comfortable while you work
  • 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.
  • 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.
  • 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.
  • Freedom & flexibility; fit your work around your life
  • 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

Nice to have

  • Designated quarterly Whaleness Days plus end of year Whaleness break

Compensation

  • Technology stipend equivalent to $100 USD net/month

Benefits

  • Home office setup
  • PTO plan that encourages you to take time to do the things you enjoy
  • Training stipend for conferences, courses and classes
  • Medical benefits, retirement and holidays vary by country
  • Equity; we are a growing start-up and want all employees to have a share in the success of the company
  • Docker's long-term vision is to become the runtime for trusted autonomy.

Company info

  • we are a growing start-up and want all employees to have a share in the success of the company
  • The more inclusive we are, the better our company will be.
  • We are a globally distributed, remote-first team building the tools that define how software gets built and delivered.

Equal opportunity

  • equal opportunity.

Visa & Work Authorization

  • Docker considers visa sponsorship on a case-by-case basis based on business needs.
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This listing is sourced directly from Docker, Inc's careers page and normalized into a canonical job model.