Machine Learning Infrastructure Engineer (Contract, Remote)

About OpenTrain

OpenTrain is the #1 platform for people who start and grow careers teaching AI. We connect AI training and data-labeling talent with projects across the industry, helping you consolidate opportunities, build a durable portfolio, and apply in minutes.

About AI training and data-labeling work

AI training (data labeling/annotation/human feedback) is the human work that helps modern models learn from examples. Contributors annotate text, code, audio, images, and more — shaping how state-of-the-art systems behave.

This work is often remote and flexible, ranging from entry-level tasks to specialist engineering roles. It’s a fast-growing way to work in tech and directly influence model quality.

• Remote-first, flexible schedule — many projects let you choose hours.
• Accessible entry points as well as higher-paying specialist roles for domain experts.

The role

OpenTrain is recruiting a Machine Learning Infrastructure Engineer for a part-time contractor engagement. This role focuses on building and operating scalable ML systems, automating end-to-end pipelines, and supporting model deployment in production.

Time commitment: 20+ hours per week. Employment type: contractor, part-time. Work location: remote, worldwide. Language: English required. Compensation: $30–$90 per hour.

What you’ll do

• Build and optimize machine learning models for production use.
• Automate end-to-end ML pipelines using CI/CD best practices.
• Design and operate scalable infrastructure on AWS to support ML applications and data pipelines.
• Orchestrate containerized workloads with Kubernetes for availability and scalability.
• Evaluate, preprocess, and frame real-world data problems for ML solutions.
• Collaborate with data scientists, engineers, and researchers to translate business needs into ML designs.
• Document technical designs, experiments, and decisions clearly for cross-functional teams.

Requirements

Candidates must be able to discuss relevant experience and show public work or a portfolio. Prior academic AI experience is not required if you can demonstrate practical ML, CI/CD, cloud, and Kubernetes expertise.

• Strong machine learning background with model development and deployment experience.
• Proficient in Python or Java.
• Hands-on experience with CI/CD workflows and automation tools.
• Practical AWS experience supporting ML applications and data pipelines.
• Advanced knowledge of Kubernetes for containerized workloads.
• Clear written and verbal communication skills in English.
• Ability to scope, structure, and solve complex, real-world data challenges.
• Portfolio or public work requested; be prepared to discuss ML, CI/CD, AWS, and Kubernetes in interviews.

Helpful background

• Familiarity with TensorFlow or PyTorch.
• Experience in high-growth startups or fast-moving engineering teams.
• Publications or open-source contributions in AI or infrastructure projects.

How applications and work proceed

Apply through OpenTrain with your profile and portfolio links. Successful applicants will discuss their machine learning and infrastructure experience and demonstrate practical problem-solving across CI/CD, AWS, and Kubernetes.

This engagement will involve work with TEXT data and labeling type COMPUTER_PROGRAMMING_CODING as noted in the project specification; labeling software is listed as OTHER. As a contractor you set availability within the 20+ hours/week expectation and are paid hourly at the agreed rate within the $30–$90/hr range.

• Employment: Contractor, part-time.
• Time requirement: 20+ hours/week (remote, worldwide).
• Compensation: Hourly rate between $30 and $90 USD.
• Data & labeling: Data type TEXT; label type COMPUTER_PROGRAMMING_CODING;