Docker AI Jobs

Discover the latest remote and onsite Docker AI roles across top active AI companies. Updated hourly.

Check out 252 new Docker AI roles opportunities posted on The Homebase

Speech Software Engineer

New
Top rated
ASAPP
Full-time
Full-time
Posted

Lead the design and implementation of a scalable, high-availability voice infrastructure that replaces legacy systems. Build and refine multi-threaded server frameworks capable of handling thousands of concurrent, real-time audio streams with minimal jitter and latency. Deploy robust ASR > LLM > TTS pipelines that process thousands of calls concurrently. Develop robust logic for handling media streams, ensuring seamless audio data flow between clients and machine learning models. Build advanced monitoring and load-testing tools specifically designed to simulate high-concurrency voice traffic. Partner with Speech Scientists and Research Engineers to integrate state-of-the-art models into a production-ready environment.

$215,000 – $235,000
Undisclosed
YEAR

(USD)

New York, United States
Maybe global
Hybrid
Python
Go
Kubernetes
Docker
AWS

Software Engineer, Backend

New
Top rated
Mashgin
Full-time
Full-time
Posted

The backend developer will own major feature development and work directly with founders on product development from end to end. Responsibilities include working with a small interdisciplinary team across hardware, software, and design to build new products from scratch; building new features and designing new architecture to address challenging problems; building backend infrastructure to perform scalable training in the cloud; rethinking and refactoring existing codebases for scale; and continuously improving and maintaining code in production. The role involves full ownership throughout the entire product lifecycle, including idea generation, design, prototyping, execution, and shipping, contributing to multiple parts of the codebase in various programming languages.

$115,000 – $210,000
Undisclosed
YEAR

(USD)

Palo Alto, United States
Maybe global
Onsite
Python
C++
Go
Java
Docker

Software Engineer, Codex Runtime

New
Top rated
OpenAI
Full-time
Full-time
Posted

The responsibilities include shaping the evolution of Codex by identifying how teams use and break AI-powered software engineering, driving changes across product, infrastructure, and model behavior to improve reliability. Building core team and enterprise primitives to enable Codex usability at scale, such as container orchestration, virtual machine provisioning/configuration, execution sandboxes, shared block storage, RBAC, admin and audit surfaces, usage and pricing controls, managed configuration and constraints, and analytics for visibility into Codex usage. Designing and owning secure, observable, full-stack systems that power Codex across web, IDEs, CLI, and CI/CD, integrating with enterprise identity and governance systems (SSO/SAML/OIDC, SCIM, policy enforcement), and developing data-access patterns that are performant, compliant, and trustworthy. Leading real-world deployments and launches by working with customers and go-to-market teams to roll out Codex across teams, using live usage and operational signals to iterate and improve the product and platform based on real-world feedback.

$255,000 – $325,000
Undisclosed
YEAR

(USD)

San Francisco, United States
Maybe global
Onsite
Python
Go
Kubernetes
Docker
CI/CD

Principal Software Architect

New
Top rated
HackerOne
Full-time
Full-time
Posted

As a Principal Software Architect at HackerOne, you will define and evolve the architectural vision for the HackerOne Platform and core systems to ensure scalability, reliability, and performance. You will partner with Product, Platform, and Security teams to translate long-term business and product goals into actionable architectural strategies. You will collaborate with Principal and Distinguished Engineers to align on technical direction, establish shared standards, and evolve system design principles. Your role involves leading major cross-team initiatives to modernize architecture, improve observability, and reduce complexity. You will mentor and guide engineering teams to foster technical excellence, knowledge sharing, and continuous improvement. You will evaluate and integrate emerging technologies including AI, GenAI, and LLM-driven architectures to enhance platform intelligence. Additionally, you will drive architectural governance and documentation to ensure maintainability and transparency and communicate architectural direction clearly to technical and non-technical stakeholders. Within the first 30-90 days, you will move from understanding systems and architecture to leading architectural initiatives that impact teams company-wide.

$230,000 – $255,000
Undisclosed
YEAR

(USD)

Washington, United States
Maybe global
Remote
JavaScript
TypeScript
Python
CI/CD
AWS

Freelance Software Developer (Kotlin) - AI Trainer

New
Top rated
Mindrift
Part-time
Full-time
Posted

As an AI Tutor in Coding specializing in Kotlin development, the responsibilities include designing high-quality technical content, examples, and explanations demonstrating best practices in Kotlin development; collaborating with engineers to ensure accuracy and consistency across code samples, tutorials, and developer guides; exploring modern Kotlin frameworks and tools to create practical, real-world examples for learning and testing; and continuously refining content based on feedback, emerging patterns, and advances in the Kotlin ecosystem. The role also involves contributing to projects aligned with skills by creating training prompts and refining model responses to help shape the future of AI while ensuring technology benefits everyone.

$80 / hour
Undisclosed
HOUR

(USD)

United States
Maybe global
Remote
Python
Docker
Kubernetes
AWS
GCP

Senior Machine Learning Engineer

New
Top rated
PhysicsX
Full-time
Full-time
Posted

Take part in building a platform used by Data Scientists and Simulation Engineers to build, train and deploy Deep Physics Models. Work on a focused, stream-aligned and cross-functional team (back-end, front-end, design) that is empowered to make its implementation decisions towards meeting its objectives. Gather and leverage domain knowledge and experience from the Data Scientists and Simulation Engineers using your product.

Undisclosed

()

Singapore
Maybe global
Hybrid
Python
Go
MLOps
Docker
Kubernetes

Senior Forward Deployed Software Engineer

New
Top rated
PhysicsX
Full-time
Full-time
Posted

Take part in building a platform used by Data Scientists and Simulation Engineers to build, train and deploy Deep Physics Models. Work on a focused, stream-aligned and cross-functional team (back-end, front-end, design) empowered to make implementation decisions towards meeting its objectives. Gather and leverage domain knowledge and experience from Data Scientists and Simulation Engineers using the product.

Undisclosed

()

Singapore
Maybe global
Hybrid
Python
Go
Docker
Kubernetes
CI/CD

Senior CFD Engineer

New
Top rated
PhysicsX
Full-time
Full-time
Posted

Take part in building a platform used by Data Scientists and Simulation Engineers to build, train and deploy Deep Physics Models. Work on a focused, stream-aligned and cross-functional team (back-end, front-end, design) that is empowered to make its implementation decisions towards meeting its objectives. Gather and leverage domain knowledge and experience from the Data Scientists and Simulation Engineers using your product.

Undisclosed

()

Singapore
Maybe global
Hybrid
Python
Go
Docker
Kubernetes
CI/CD

Principal Machine Learning Engineer

New
Top rated
PhysicsX
Full-time
Full-time
Posted

The role involves building a platform used by Data Scientists and Simulation Engineers to build, train, and deploy Deep Physics Models. The candidate will work on a focused, stream-aligned, and cross-functional team that includes back-end, front-end, and design members, empowered to make its own implementation decisions towards meeting its objectives. Responsibilities include gathering and leveraging domain knowledge and experience from the Data Scientists and Simulation Engineers using the product, taking ownership of work from implementation to production, ensuring quality, scalability, and observability at every step, which includes testing, containerization, continuous integration and delivery, authentication, authorization, telemetry, observability, and monitoring.

Undisclosed

()

Singapore
Maybe global
Hybrid
Python
Go
Docker
Kubernetes
CI/CD

Principal Forward Deployed Software Engineer

New
Top rated
PhysicsX
Full-time
Full-time
Posted

Take part in building a platform used by Data Scientists and Simulation Engineers to build, train and deploy Deep Physics Models. Work on a focused, stream-aligned and cross-functional team (back-end, front-end, design) that is empowered to make its implementation decisions towards meeting its objectives. Gather and leverage domain knowledge and experience from the Data Scientists and Simulation Engineers using your product.

Undisclosed

()

Shoreditch, Singapore
Maybe global
Hybrid
Python
Go
Docker
Kubernetes
CI/CD

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[{"question":"What are Docker AI jobs?","answer":"Docker AI jobs involve developing, deploying, and maintaining AI applications using containerization technology. These positions focus on creating reproducible AI workflows, packaging machine learning models with dependencies, and ensuring consistent execution across environments. Professionals in these roles typically work on MLOps pipelines, containerized AI applications, and implement solutions that seamlessly transition from development to production."},{"question":"What roles commonly require Docker skills?","answer":"Machine Learning Engineers, Data Scientists, AI Developers, and DevOps Engineers working on AI systems commonly require containerization skills. These professionals use containers to package models, ensure reproducibility, and streamline deployment pipelines. Full-stack developers building AI-powered applications and MLOps specialists implementing continuous integration workflows also frequently need proficiency with containerized environments and deployment strategies."},{"question":"What skills are typically required alongside Docker?","answer":"Alongside containerization expertise, employers typically seek proficiency in AI frameworks like TensorFlow, PyTorch, and Hugging Face. Familiarity with Docker Compose for multi-container applications, version control systems, and CI/CD pipelines is essential. Additional valuable skills include YAML configuration, cloud deployment knowledge, GPU acceleration techniques, and experience with MLOps practices that facilitate model development, testing, and production deployment."},{"question":"What experience level do Docker AI jobs usually require?","answer":"AI positions requiring containerization skills typically seek mid-level professionals with 2-4 years of practical experience. Entry-level roles may accept candidates with demonstrated proficiency in basic container commands, Dockerfile creation, and image management. Senior positions often demand extensive experience integrating containers into production ML pipelines, optimizing container resources, and implementing advanced deployment strategies across cloud and edge environments."},{"question":"What is the salary range for Docker AI jobs?","answer":"Compensation for AI professionals with containerization expertise varies based on location, experience level, industry, and additional technical skills. Junior roles typically start at competitive market rates, while senior positions command premium salaries. The most lucrative opportunities combine deep learning expertise, container orchestration experience, and cloud platform knowledge. Specialized industries like finance or healthcare often offer higher compensation for these in-demand skill combinations."},{"question":"Are Docker AI jobs in demand?","answer":"Containerization skills remain highly sought after in AI development, with strong demand driven by organizations implementing MLOps practices and scalable AI deployment strategies. Recent partnerships like Anaconda-Docker and trends in serverless AI containers have intensified hiring needs. The emergence of specialized tools like Docker Model Runner, Docker Offload, and Docker AI Catalog reflects the growing importance of containerized workflows in modern AI development and deployment practices."},{"question":"What is the difference between Docker and Kubernetes in AI roles?","answer":"In AI roles, containerization focuses on packaging individual applications with dependencies for consistent execution, while Kubernetes orchestrates multiple containers at scale. ML engineers might use Docker to create reproducible model environments but implement Kubernetes to manage production deployments across clusters. While containerization handles the model packaging, Kubernetes addresses the scalability, load balancing, and automated recovery needed for production AI systems serving multiple users simultaneously."}]