We're looking for experienced ML engineers based in or around New York to evaluate AI-generated machine learning solutions — catching errors, improving quality, and helping frontier AI models get genuinely better at one of the hardest things they do.
What if your machine learning expertise could directly influence how the most advanced AI systems in the world think, reason, and write code?
This is a fully remote, flexible contract role. Work asynchronously on your own schedule, from wherever you are. No fixed hours, no meetings — just high-impact, expert work that matters.
Why Join Us
Work on cutting-edge AI projects alongside leading research labs and top AI teams.
Fully remote and async — work when and where it suits you, with no minimum hour commitments beyond project needs.
Freelance autonomy with the structure of meaningful, task-based work.
Your contributions directly improve AI models used by top research labs and enterprise teams worldwide.
High-performing contributors take on expanded responsibilities and lead new programs.
Potential for ongoing work and contract extension as new projects launch.
Responsibilities
Review and evaluate AI-generated machine learning code — including Python, TensorFlow, PyTorch, and scikit-learn — for correctness, efficiency, scalability, and clarity.
Write high-quality ML solutions to modeling, data processing, and deployment problems across a range of difficulty levels.
Craft clear, developer-friendly explanations for model architecture decisions, code logic, and problem-solving approaches.
Identify edge cases, ambiguities, and weaknesses in problem statements, datasets, or AI-generated responses.
Help set the quality bar for how AI understands and produces machine learning code.
Required skills
Deeply fluent in machine learning — you know your way around model development, data preprocessing, training pipelines, and deployment.
Strong written communicator — able to explain complex ML concepts clearly and precisely.
Detail-oriented and rigorous — you catch what others miss and care about getting things right.
Self-motivated and comfortable working independently in an async environment.
Preferred skills
3–5+ years working on machine learning projects, pipelines, or MLOps.
Experience with model evaluation, cloud deployment, or production ML systems.
Bachelor's, Master's, or PhD in Computer Science, Machine Learning, or a related field.
Background in data labeling, RLHF, or other AI training workflows.
Prior experience with code review or technical writing.
Experience and education
Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
Thriveth makes AI data-training work easier to find, understand, and navigate. We replace uncertainty with clear opportunities, realistic expectations, and insights from real application journeys.
Hiring companyAlignerr
