Staff ML Engineer

DockerYesterday

Location

Palo Alto, CA

Workplace

Remote

Type

Full Time

Salary

USD 205,000 – 330,000

Level

Staff

Role

Staff ML Engineer

Posted

Jun 12, 2026

Full TimeRemoteStaff

The role

Summary

Docker is seeking a Staff ML Engineer to join their Intelligence team, focusing on building cutting-edge ML systems for governance and security capabilities. The ideal candidate will be a hands-on technical leader who can design, implement, and ship advanced machine learning solutions that enhance Docker's platform for trusted autonomous workflows.

What you'll do

ML System Design: Design and implement machine learning systems for governance and security capabilities

Infrastructure Development: Build comprehensive ML infrastructure including data pipelines, feature stores, and model serving systems

Technical Leadership: Set technical direction for ML work, define architecture, and establish evaluation methodologies

Model Lifecycle Management: Develop and maintain robust processes for model training, evaluation, and deployment

Team Growth: Contribute to team recruitment, mentorship, and organizational scaling

What we look for

Technical

ML Expertise5+ years of deep applied ML/AI expertise with production system experience

Software Engineering8+ years of professional software engineering experience in backend or infrastructure roles

Education

Computer Science DegreeBachelor's degree in Computer Science, Engineering, or related field preferred

Experience

Production MLProven track record of building and owning end-to-end ML systems

LLM SystemsExperience with Large Language Model evaluation, prompt engineering, and production deployment

Skills

Required skills

Machine LearningDeep expertise in designing, training, and deploying production ML systems

AI SafetyExperience with fraud detection, security, and trust domains

Large Language ModelsProficiency in LLM-based systems, prompt engineering, and evaluation

Backend EngineeringStrong software engineering skills with infrastructure and platform experience

Data PipelinesAbility to build and manage ML data infrastructure, feature stores, and model serving

Nice to have

Agent FrameworksFamiliarity with autonomous agent ecosystems and multi-agent systems

Adversarial MLExperience with detecting and mitigating adversarial attacks in ML systems

AI GovernanceUnderstanding of policy, identity, and audit mechanisms for AI systems

Compensation & benefits

Salary

USD 205,000 – 330,000 (annual)

Stock options

Available

Benefits

Flexible Work

Remote-first culture with work flexibility

Parental Leave

16 weeks of paid parental leave after 6 months of employment

Technology Stipend

$100 monthly technology allowance

Professional Development

Training stipend for conferences, courses, and classes

Equity

Stock options to share in company success

Home Office Setup

Support for comfortable home office environment

Time Off

Quarterly Whaleness Days and end-of-year Whaleness break

Interview process

1
Initial Screening — HR phone screen to assess basic qualifications and role fit
2
Technical Phone Interview — Detailed discussion of ML and software engineering background
3
ML Systems Design Challenge — In-depth technical interview focusing on ML architecture and problem-solving
4
Onsite/Virtual Panel — Multiple interviews with team members covering technical skills, system design, and cultural fit
5
Final Leadership Interview — Discussion with senior leadership about team vision and candidate's potential impact