Remote positions

Remote Docker Jobs

Browse remote Docker positions — containerisation for AI systems, MLOps infrastructure, and DevOps engineering at AI-first companies.

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MLOps Engineer DevOps for AI Platform Engineer Infrastructure Engineer Containerisation Specialist

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Jobs & Projects

Notion

Posted 1 month ago

Forward Deployed Engineer, India

Notion

Hyderabad, India

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Full-time
English
Full page
Cerebras

Posted 2 months ago

Application Security Engineer

Cerebras

Sunnyvale, CA

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Full-time
English
Full page
Replit

Posted 2 months ago

AI Agent Security Architect

Replit

Foster City, CA

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Full-time
English
Full page
Cerebras

Posted 2 months ago

Cluster Operations Software Engineer

Cerebras

Sunnyvale, CA

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Full-time
English
Full page
Baseten

Posted 2 months ago

Software Engineer - AI Developer Productivity

Baseten

San Francisco

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Full-time
English
$165K – $330K / year
Full page
Baseten

Posted 2 months ago

Software Engineer - Testing Frameworks

Baseten

San Francisco

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Full-time
English
$165K – $330K / year
Full page
Character.AI

Posted 3 months ago

Software Engineer, Backend

Character.AI

Redwood City, CA

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Full-time
English
$180K – $300K / year
Full page
Character.AI

Posted 3 months ago

Research Engineer, Post-Training (All Industry Levels)

Character.AI

Redwood City or New York City

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Full-time
English
$225K – $400K / year
reinforcement learning docker kubernetes machine learning llm fine-tuning
Full page
Character.AI

Posted 3 months ago

Research Engineer, AI Safety & Alignment

Character.AI

Redwood City, CA

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Full-time
English
$225K – $400K / year
reinforcement learning docker kubernetes machine learning machine learning +2 more
Full page
Replit

Posted 3 months ago

Security Engineer - Vuln Management (Infra)

Replit

Foster City, CA

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Full-time
English
$210K – $270K / year
Full page

Role guide

What to expect in remote Docker jobs

Docker is the foundation of modern AI deployment infrastructure. Remote Docker jobs at AI companies involve containerising ML models, building reproducible training environments, and managing deployment pipelines. Engineers with Docker experience who also understand ML workflows are particularly in demand.

What you'll work on

  • Containerise ML models for reproducible, portable deployment
  • Build multi-stage Docker images that keep model serving images lean
  • Create development environments that match production exactly
  • Orchestrate AI microservices across training and inference containers

What companies look for

  • Multi-stage Dockerfile design for ML workloads
  • Docker Compose for local development and testing environments
  • Experience with GPU container configurations for model training

Frequently asked questions

What Docker skills do AI companies typically require?

Multi-stage builds, GPU container configuration, Docker Compose for local development, and integration with CI/CD pipelines. MLOps-focused roles often require Kubernetes knowledge on top of Docker.

Can I get a remote Docker job without Kubernetes experience?

Yes — especially at smaller companies or for roles focused on development environments rather than production orchestration. As companies scale, Kubernetes becomes increasingly expected.

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