Docker has been one of the most loved brands in developer tooling trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the worlds 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.

We are a globally distributed remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development Docker is at the center of that shift providing the sandboxed environments verified images and secure infrastructure that make autonomous workflows trustworthy by default.

Dockers long-term vision is to become the runtime for trusted autonomy. As agents become more capable and autonomous governance policy identity and audit become foundational.

The Intelligence team builds intelligence-driven product capabilities that make software and agent execution on Docker safer more effective more trustworthy and more efficient. Because Docker sits at the intersection of models tools software identities credentials networks and execution we have visibility into behavior and context few other platforms can see and we think that visibility is the foundation for a new layer of value across the platform.

About the role

Were hiring a ML Engineer as one of the founding engineers on Intelligence Org. Youll work directly with the teams 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: youll 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 teams 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 years of professional hands-on full-time software engineering experience in backend infrastructure or platform engineering.

• Bachelors degree in Computer Science Engineering or a related field or equivalent practical experience

• Youve 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 cant 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.

• Youre 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

Docker embraces diversity and equal opportunity. We are committed to building a team that represents a variety of backgrounds perspectives and skills. The more inclusive we are the better our company will be.

#LI-REMOTE

Required Experience:

IC