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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Remote worldwide
All job types
MLOps Engineer DevOps for AI Platform Engineer Infrastructure Engineer Containerisation Specialist

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Jobs & Projects

Sourcegraph

Posted 1 week ago

ML & Agentic Systems Engineer [IC4]

Sourcegraph

Remote

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Full-time
English
machine learning docker llm statistics typescript +2 more
Full page
Runpod

Posted 2 weeks ago

Technical Support Engineer (L1)

Runpod

Remote - USA

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Full-time
English
python docker sql llm fine-tuning
Full page
Supabase

Posted 2 weeks ago

Software Engineer - Storage

Supabase

Remote, Global

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Full-time
English
Full page
ClickHouse

Posted 2 weeks ago

Engineering Manager - Control Plane Platform Engineer

ClickHouse

Europe or US

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Full-time
English
$205K – $250K / year
Full page
Vannevar Labs

Posted 2 weeks ago

DevOps Engineer

Vannevar Labs

Remote; Washington, District of Columbia, United States

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Full-time
English
Full page
Zapier

Posted 2 weeks ago

Sr. Engineer, Infrastructure Security

Zapier

NAMER

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senior
Full-time
English
$174K – $261K / year
Full page
Brain Co.

Posted 2 weeks ago

AI Security Engineer, 2027 New Grad

Brain Co.

San Francisco Bay Area

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Full-time
English
Full page
Snowflake

Posted 2 weeks ago

Staff Designated Support Engineer

Snowflake

IE-Dublin-WW

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staff
Full-time
English
Full page
Cerebras

Posted 3 weeks ago

Infrastructure Systems Engineer – Linux, Storage & Automation

Cerebras

Sunnyvale, CA

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Full-time
English
Full page
ClickHouse

Posted 3 weeks ago

Langfuse - Senior Backend Engineer (US-East)

ClickHouse

New York

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senior
Full-time
English
docker typescript
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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