ML Engineer

Docker2 days ago

Location

Palo Alto, CA

Workplace

Remote

Type

Full Time

Salary

USD 138,500 – 225,500

Level

Senior

Role

ML Engineer

Posted

Jun 15, 2026

Full TimeRemoteSenior

The role

Summary

Docker is seeking a senior-level Machine Learning Engineer to join their Intelligence team, focusing on building advanced AI-driven security and governance capabilities for container environments. The role involves developing cutting-edge ML systems that enhance Docker's platform security, with a particular emphasis on creating intelligent, trustworthy autonomous workflows.

What you'll do

ML System Development: Design, train, evaluate, and deploy ML systems for governance and security capabilities, including prompt injection detection, behavioral anomaly detection, and trust scoring

Infrastructure Engineering: Build and maintain supporting ML infrastructure including data pipelines, feature stores, model serving, and evaluation harnesses

Technical Leadership: Set technical direction for ML work, own system architecture, evaluation methodology, and model lifecycle management

Strategic Decision Making: Make pragmatic build-vs-buy decisions, leveraging frontier models and managed services while identifying opportunities for custom system development

Team Development: Participate in recruiting, mentoring, and team growth for the Intelligence organization

Operational Responsibility: Potentially participate in 24/7 on-call rotation for the Agentic Platform, maintaining service reliability and performance

What we look for

Technical

Machine Learning ExpertiseDeep applied ML/AI expertise with proven track record of shipping production systems, especially in fraud, abuse, safety, security, or trust domains

Software Engineering SkillsMinimum 4+ years of professional backend, infrastructure, or platform engineering experience

ML InfrastructureExperience building and owning complete ML system ecosystems, including data pipelines, model serving, evaluation, and monitoring

AI Technology ProficiencyAdvanced experience with LLM-based systems, including evaluation, prompt engineering, fine-tuning, retrieval, and agent frameworks

Education

Academic BackgroundBachelor's degree in Computer Science, Engineering, or related field; equivalent practical experience acceptable

Experience

Professional Experience5+ years of applied ML/AI expertise with production system deployment

Domain ExpertiseExperience in handling adversarial dynamics, imbalanced data, and high-stakes decision-making environments

Skills

Required skills

Machine LearningAdvanced ML model development, training, and deployment skills

ProgrammingProficient in Python, with strong software engineering capabilities

AI TechnologiesExpertise in Large Language Models, prompt engineering, and AI safety techniques

Nice to have

Cloud PlatformsExperience with AWS, GCP, or Azure ML services

Container TechnologiesDeep understanding of containerization and Docker ecosystem

Compensation & benefits

Salary

USD 138,500 – 225,500 (annual)

Stock options

Available

Benefits

Remote Work

Fully remote-first culture with flexible work arrangements

Parental Leave

16 weeks of paid parental leave after 6 months of employment

Technology Stipend

$100 monthly technology allowance for home office setup

Professional Development

Training stipend for conferences, courses, and classes

Equity

Stock options to share in company's growth and success

Interview process

1
Initial Screening — HR review of application and initial qualifications
2
Technical Phone Screen — Detailed discussion of ML engineering experience and technical capabilities
3
Technical Interviews — Multiple rounds of in-depth technical interviews focusing on ML systems design, coding, and problem-solving
4
Hiring Manager Interview — Strategic discussion about team fit, technical vision, and role expectations
5
Final Interview — Comprehensive evaluation of technical skills, team compatibility, and overall potential contribution