Software Engineer – Machine Learning (AI Training)

Alignerr is seeking experienced Machine Learning engineers in the Netherlands to evaluate and improve AI-generated ML code and solutions. This is a fully remote, flexible hourly contract role focused on reviewing Python, TensorFlow, PyTorch, and scikit-learn code, writing high-quality ML solutions, and helping frontier AI models improve. Candidates need deep ML expertise, strong written communication, and a detail-oriented, self-motivated approach.

Core AIRemoteContractMid LevelMachine LearningPython

Software Engineer – Machine Learning (AI Training)

Alignerr is seeking experienced Machine Learning engineers in the Netherlands to evaluate and improve AI-generated ML code and solutions. This is a fully remote, flexible hourly contract role focused on reviewing Python, TensorFlow, PyTorch, and scikit-learn code, writing high-quality ML solutions, and helping frontier AI models improve. Candidates need deep ML expertise, strong written communication, and a detail-oriented, self-motivated approach.

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Core AIRemoteContractMid LevelMachine Learning

Salary

Not specified

Work Location

Amsterdam, North Holland, Netherlands, NL

Work Model

Fully remote, flexible contract role; work asynchronously on your own schedule, no fixed hours, no meetings

Experience Required

5 years

Employment Type

Hourly Contract

Experience Level

3–5+ years working on machine learning projects, pipelines, or MLOps

Core Qualifications

Technical (Must-have)

Machine LearningPythonTensorFlowPyTorchscikit-learnModel developmentData preprocessingTraining pipelinesDeployment

Soft Skills

Strong written communicationDetail-orientedRigorousSelf-motivatedIndependent working

Preferred Qualifications

Technical (Nice-to-have)

MLOpsModel evaluationCloud deploymentProduction ML systemsData labelingRLHFAI training workflowsCode reviewTechnical writing

Key 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

Machine LearningAI TrainingContractRemotePythonTensorFlowPyTorchscikit-learnMLOpsNetherlands