Docker

ML Engineer

Docker • $130K — $180K *
Palo Alto, CA 94303In-Person
Enterprise Technology
5 - 7 years of experience
Today
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Job Overview by Ladders

Qualifications

  • 5+ years of deep applied ML/AI expertise with a solid record in production systems.
  • 4+ years of backend, infrastructure, or platform engineering experience.
  • Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
  • Experience building and owning ML systems, including data pipelines and monitoring.
  • Proficiency with modern AI tools and understanding of when to leverage frontier models.
  • Knowledge of LLM-based systems and the agent/MCP ecosystem.
  • Comfortable with ambiguity and adept at making decisions with limited information.
  • Collaborative mindset, strong communication skills.

Responsibilities

  • Design, train, evaluate, and implement ML systems for governance and security.
  • Build infrastructure including data pipelines and model serving.
  • Make strategic build-vs-buy decisions to optimize development speed.
  • Set the technical direction and ownership of the ML architecture and methodology.
  • Mentor team members and assist in team growth.
  • Participate in 24/7 on-call rotation for system reliability.

Benefits

  • Flexible work arrangements to fit your lifestyle.
  • Quarterly Whaleness Days and an end-of-year break.
  • Home office setup for comfortable work conditions.
  • 16 weeks of paid parental leave after 6 months.
  • Technology stipend of $100 net/month.
  • Generous PTO plan to encourage personal time off.
  • Training stipend for professional development opportunities.
  • Equity options available as part of start-up growth.
  • Docker Swag to represent the brand.
  • Comprehensive medical benefits and retirement plans, varying by country.
Full Job Description
About the role

We're hiring a ML Engineer as one of the founding engineers on Intelligence Org. You'll work directly with the team's first engineers and manager to figure out what to build, how to build it, and how it fits into the broader Docker platform. 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.
  • 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


Qualifications
  • 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+ yearsof 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.


Docker considers visa sponsorship on a case-by-case basis based on business needs.

Perks
  • 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


#LI-REMOTE

About Docker

Docker is a software company that provides an open platform for developers and sysadmins to build, ship, and run distributed applications. The company was founded in 2013 and is headquartered in San Francisco, California. Docker's platform allows developers to package their applications and dependencies into a single container, which can then be easily deployed to any environment. This makes it easier for developers to build and deploy applications, and helps to reduce the time and cost associated with managing complex application environments. Docker has a global presence, with operations in North America, Europe, and Asia.
Learn more about Docker
Size
1,000 employees
Industry
Enterprise Technology
Founded
2010
* Ladders Estimates

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