Docker

1 month ago

Staff ML Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Hands-on Staff ML Engineer on the Intelligence org who will shape technical direction, ship initial intelligence capabilities, and build foundations (data, evaluation, infrastructure) for Docker's platform. You’ll design and deploy ML systems for governance and security, develop supporting data pipelines and serving infrastructure, and help recruit and mentor a growing team in an early-stage setting.

Location: Palo Alto, Seattle

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Sr. Manager level

Key Responsibilities

•Design, train, evaluate, and ship ML systems that power governance and security capabilities (e.g., prompt injection detection, behavioral anomaly detection, trust scoring, policy recommendations).
•Build the supporting infrastructure: data pipelines, feature stores, model serving, evaluation harnesses, and fast feedback loops.
•Make pragmatic build-vs-buy calls using frontier models, off-the-shelf tooling, and managed services while investing in custom systems where advantageous.
•Set technical direction for the team's ML work: architecture, evaluation methodology, model lifecycle, and shipping bar.
•Help recruit, mentor, and shape the team as it grows; participate in 24/7 on-call rotation as needed.

Pay and Benefits

Salary: USD 205,000 - 330,000 annually

Equity and Bonus:Equity

Perks:EquityRemote WorkHealth InsuranceParental LeaveTechnology Stipend

Key Requirements

•5+ years of deep applied ML/AI expertise with a track record of shipping production systems in fraud, abuse, safety, security, or trust domains.
•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.
•Built and owned ML systems end-to-end (data pipelines, serving, evaluation, monitoring) and shipped customer-facing products.
•Experience with LLM-based systems in production (evaluation, prompt engineering, fine-tuning, retrieval, guardrails, agent frameworks) and familiarity with the agent/MCP ecosystem.

Experience:AIMLSoftware

Education:Bachelor's

Skills:CollaborationCommunicationMentorshipProblem-solvingLeadership

Tech Stack:LLMsPrompt engineeringModel servingData pipelinesFeature storesEvaluation

Company Brief

Docker

Docker builds developer tools and a collaborative platform for building, sharing and running containerized applications, including Docker Desktop and Docker Hub, to simplify container workflows from code to cloud.

Industry: Developer Tools

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Funding: Series C

Headquarters: San Francisco, United States

Founded: 2013

Glassdoor: 2.7

Website LinkedIn Glassdoor

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Docker

1 month ago

Staff ML Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: Palo Alto, Seattle

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Sr. Manager level

Key Responsibilities

•Design, train, evaluate, and ship ML systems that power governance and security capabilities (e.g., prompt injection detection, behavioral anomaly detection, trust scoring, policy recommendations).
•Build the supporting infrastructure: data pipelines, feature stores, model serving, evaluation harnesses, and fast feedback loops.
•Make pragmatic build-vs-buy calls using frontier models, off-the-shelf tooling, and managed services while investing in custom systems where advantageous.
•Set technical direction for the team's ML work: architecture, evaluation methodology, model lifecycle, and shipping bar.
•Help recruit, mentor, and shape the team as it grows; participate in 24/7 on-call rotation as needed.

Pay and Benefits

Salary: USD 205,000 - 330,000 annually

Equity and Bonus:Equity

Perks:EquityRemote WorkHealth InsuranceParental LeaveTechnology Stipend

Key Requirements

•5+ years of deep applied ML/AI expertise with a track record of shipping production systems in fraud, abuse, safety, security, or trust domains.
•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.
•Built and owned ML systems end-to-end (data pipelines, serving, evaluation, monitoring) and shipped customer-facing products.
•Experience with LLM-based systems in production (evaluation, prompt engineering, fine-tuning, retrieval, guardrails, agent frameworks) and familiarity with the agent/MCP ecosystem.

Experience:AIMLSoftware

Education:Bachelor's

Skills:CollaborationCommunicationMentorshipProblem-solvingLeadership

Tech Stack:LLMsPrompt engineeringModel servingData pipelinesFeature storesEvaluation

Company Brief

Docker

Industry: Developer Tools

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Funding: Series C

Headquarters: San Francisco, United States

Founded: 2013

Glassdoor: 2.7

Website LinkedIn Glassdoor