Open AI training and model evaluation roles that call for ML Infrastructure expertise, gathered from 4 platforms. Part of Software Engineering.
Pay figures cover the 42 open jobs that publish an hourly rate in USD. They are published rates, not a guarantee of income. Last checked on October 8, 2026.
This role involves designing and building server-side systems, APIs, and data pipelines for AI infrastructure. Back end developers will optimize scalable microservices and databases to support AI training and inference workloads on a remote, flexible contract basis.
This role involves designing and optimizing high-performance C backend systems and data pipelines for AI model training and evaluation. The position is ideal for experienced full-stack engineers who want to build production-grade infrastructure used by leading AI research organizations.
This role involves designing and optimizing Python-based backend systems for data annotation, validation, and AI model training infrastructure. The position requires a senior full-stack engineer to build high-performance data pipelines, asynchronous task queues, and evaluation systems used by leading AI labs.
This role involves building and optimizing high-performance backend systems and tooling in Rust to support AI data pipelines, annotation workflows, and evaluation systems. You will work on production infrastructure that powers advanced AI model training, collaborating with research and engineering teams on scalable solutions.
A senior C++ engineer will design and build high-performance data pipelines, annotation tooling, and evaluation infrastructure for AI systems. The role involves optimizing backend services for large-scale data processing and quality control in support of model training and validation.
Design and build high-performance C++ systems for AI data pipelines, evaluation workflows, and internal tooling. This role involves optimizing production codebases, developing backend services for data annotation and quality control, and collaborating with research teams to support model training infrastructure.
This role involves designing and optimizing high-performance C++ systems for AI infrastructure, including data pipelines, annotation tooling, and evaluation workflows. The position is ideal for senior C++ engineers who specialize in performance optimization and want to contribute to cutting-edge AI research infrastructure.
A senior C# engineer will design and build high-performance data pipelines, annotation tooling, and evaluation systems for AI model training. The role involves full-stack backend development, system optimization, and collaboration with data and research teams to support production infrastructure for AI labs.
A senior C++ engineer is needed to design and optimize high-performance data pipelines, annotation tooling, and evaluation systems for leading AI research teams. This fully remote contract role involves full-stack development, system optimization, and collaboration with data and research teams on production-grade infrastructure.
Design and build high-performance Rust systems for AI data infrastructure, including data pipelines, annotation tooling, and evaluation systems that support large-scale AI research. This is a fully remote contract role for senior engineers with deep expertise in systems optimization and concurrent programming.
This is a backend engineering role focused on building and optimizing server-side infrastructure for AI systems. The position involves designing scalable APIs, data pipelines, and microservices that power machine learning and AI products, working remotely on a flexible hourly contract basis.
This is a contract role for back end developers to design, build, and optimize server-side systems and APIs that power AI infrastructure, including data pipelines and model-serving infrastructure. The position is fully remote and flexible, targeting engineers in Brazil who want to work on scalable, high-performance systems supporting AI training and inference workloads.
Design and evaluate infrastructure and automation challenges to train and benchmark AI systems used by leading research labs and Fortune 500 companies. This remote contract role is for experienced DevOps engineers to create realistic cloud infrastructure scenarios, write Infrastructure as Code, and assess how well AI models understand and reason about complex DevOps concepts.
This role involves writing, debugging, and evaluating AI-generated code to help train and improve AI coding assistants. Software engineers will review code quality, identify bugs and security issues, provide detailed feedback, and design test scenarios to stress-test AI capabilities across various programming languages and frameworks.
This role involves designing, building, and scaling infrastructure systems that power AI products and services. Senior software engineers will work on production-grade systems supporting AI training, evaluation, and deployment pipelines, writing clean and performant code while collaborating with ML engineers and researchers in a remote, autonomous environment.
This remote contract role centers on designing, building and scaling the backend systems, APIs and data pipelines that support AI model training, evaluation and deployment. It suits experienced software engineers who can work autonomously on production-grade systems and collaborate asynchronously with ML researchers and product managers.
This remote contract role asks a senior engineer to design, build and scale the backend systems behind AI products, including training, evaluation and deployment pipelines. It suits experienced software engineers who enjoy hard architectural problems and want to work asynchronously alongside ML researchers and product managers.
This fully remote contract role is for a senior Python engineer who builds and optimizes the data pipelines, annotation tools and evaluation systems that AI labs use to train and benchmark their models. The work is hands-on with production systems and close collaboration with research and engineering teams. It suits backend engineers with deep Python and full-stack experience who want to lead technical decisions in AI infrastructure.
This is a remote contract role for a senior Rust engineer who will design, optimize, and lead the backend systems behind AI data pipelines and model evaluation workflows. The work involves reliability, performance, and safety of production codebases, and suits experienced systems engineers who can also lead architecture discussions with research and engineering teams.
This contract role centers on building the Python infrastructure that AI labs use to prepare and assess training data, including data pipelines, annotation tools and evaluation systems. It is aimed at senior engineers with deep production Python experience who can design distributed systems and lead architecture decisions.
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FAQ
44 ML Infrastructure AI training jobs are open on SideHustler today. 1 was posted in the last 7 days. Listings are rechecked against the official postings: the latest check on this list was on October 8, 2026.
Among the 42 open roles that publish an hourly rate in USD, pay runs from $20 to $150 per hour, with a median of $63. These are the rates the platforms publish, not a guarantee of income or hours.
Alignerr (29), Mercor (10), micro1 (4) and Vetto (1). You apply on the platform itself, which handles screening, contracts and payment.
The most requested areas of expertise on these listings are ML Infrastructure, Backend Development, System Design, Code Quality & Review, Python. Each listing states its own requirements.
Apply now opens the official posting on the platform, where you complete the application. You need no account on SideHustler. To see which roles fit your background first, add your resume and every open job is scored against your profile.
