Join OpenTrain as a part-time contractor building production ML pipelines, deploying models on AWS, and orchestrating containerized workloads; remote worldwide, 20+ hrs/week, pay $30–$90/hr.
Coding & Software
100% Remote Hourly · $30–$90/hr
$30–$90/hr
Compensation
Worldwide
Eligibility
Entry
Experience
Jun 28, 2026
Posted
Open worldwide
Interested in this role?
Create a free OpenTrain account and apply in minutes.
OpenTrain is the centralized, open platform where people build careers in AI training and data labeling. We help contributors find projects, consolidate opportunities, and grow a unified AI training portfolio — all from one free account.
For this role, OpenTrain is the hiring and contracting organization. You will work directly with our engineering and data teams to deliver production-ready machine learning infrastructure and technical documentation.
About AI training and this kind of work
AI training (also called data labeling or human feedback work) is the human-driven foundation behind modern AI systems. Contributors prepare, evaluate, and shape datasets and model behavior — and many roles are flexible, remote, and accessible to people at many career stages.
This role sits at the intersection of model development, infrastructure, and data engineering: your work helps models move from experiments into reliable, scalable production.
The role
We are recruiting a Machine Learning Infrastructure Engineer to design and optimize production ML models, build CI/CD-enabled pipelines, deploy scalable infrastructure on AWS, and orchestrate containerized workloads with Kubernetes.
This is a part-time contractor opportunity (20+ hours per week), open worldwide and paid hourly. The posted rate range is USD $30–$90/hr.
Position type: Contractor, part-time, remote (worldwide).
Time commitment: 20+ hours per week.
Pay: Hourly, USD $30–$90 per hour.
What you'll do
Build and optimize machine learning models for production environments.
Implement and automate end-to-end ML pipelines using CI/CD best practices.
Deploy and manage scalable AI infrastructure on AWS.
Orchestrate containerized workloads with Kubernetes for availability and scaling.
Collaborate with data scientists, engineers, and researchers to frame real-world ML problems.
Evaluate, preprocess, and prepare data for modeling and fine-tuning.
Write clear technical documentation describing solutions and decisions.
Requirements
Candidates must be able to demonstrate hands-on experience with ML model development and deployment and clear technical communication skills. The role expects practical ability to scope and solve complex data problems.
Proven machine learning expertise including model development and deployment.
Strong programming skills in Python or Java.
Hands-on experience with AWS services for ML applications and data pipelines.
Advanced knowledge of Kubernetes for container orchestration.
Experience with CI/CD workflows and automation tools.
Ability to evaluate, structure, and solve real-world data challenges.
Strong written and verbal communication and documentation skills.
Helpful background
Familiarity with TensorFlow or PyTorch.
Experience working in high-growth or startup environments.
Publication record or contributions to open-source AI projects.
Experience supporting fine-tuning or coding-related labeling projects (FINE_TUNING, COMPUTER_PROGRAMMING_CODING).
How it works and how to apply
Create a free OpenTrain account to apply. You will be assessed on technical skills and past ML projects; selected contractors onboard to our systems and begin collaborating with engineering teams.
OpenTrain manages contracting and payments for this role. Because this is remote and part-time, you can shape your schedule while contributing to production ML infrastructure and data workflows.
Apply through your OpenTrain profile and include examples of ML projects or deployments.
Work is remote and contracted through OpenTrain; payments are hourly within the stated range.
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