Staff Machine Learning Engineer, Docker
$205-330k
+ Equity
More information about location
Office located in Palo Alto, CA
App development platform
Be an early applicant
App development platform
1001+ employees
Be an early applicant
$205-330k
+ Equity
More information about location
Office located in Palo Alto, CA
1001+ employees
Company mission
To simplify the lives of developers building world-changing apps.
Role
Who you are
- 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
- 8+ 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
What the job involves
- We're hiring a Staff 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
- 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
Our take
Docker supplies a hub and desktop solution to simplify the workflow of app development teams. Originally known for popularising the idea of containerising software, it saw itself outpaced by Kubernetes. However, the company has identified a problem with the growing complexity of containerisation, with some apps consisting of dozens or even hundreds of containers - which is what it now addresses.
Docker has had a difficult time in the past, with 2019 seeing it sell off its enterprise business, reduce its workforce by hundreds, and change its leadership team. As a well known brand and ecosystem for containerisation, however, it aims to lure developers back to its product as well as to take advantage of the growing global demand for app development.
Returning to focus on developers rather than large companies was certainly a gamble, but one that seems to have paid off. The company has returned to profitability and raised Series C funding in 2022, which has been used to hire new talent, ramping up its business, and continuing to develop and refine its product. On top of this bounce back to success, it's also embarked on a series of acquisitions to bolster its business.
Steph
Company Specialist at Welcome to the Jungle
Insights
47% employee growth in 12 months
Company
Funding (last 2 of 13 rounds)
Mar 2022
$105m
SERIES C
Mar 2021
$23m
SERIES B
Total funding: $526m
Company benefits
- 100% company paid medical premiums for employees and dependents
- Flexible Time Off Policy
- Employer Paid Holidays
- Generous Parental Leave (after 6 months of employment)
- Home Office Set Up Budget
- Monthly Technology Stipend
- Training Allowances
- Life and Disability Insurance
- Retirement Plans
- Virtual and In-Person Social Events
- Docker Swag
- Quarterly Hackathons
Company HQ
China Basin, San Francisco, CA
Leadership
Don Johnson
(CEO)Prior to joining Docker in 2025, Don spent nearly 9 years at Oracle in various Engineering/VP roles. Before that, they spent over 7 years at Amazon as a Software Development Engineer and Principal Engineer.
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