Software Engineer – Machine Learning (AI Training)

Alignerr Corp.; Amsterdam; Remote; EUR 55,000 - 110,000; Part time

Job summary

Alignerr is seeking experienced ML engineers in Amsterdam and across the Netherlands to evaluate AI-generated machine learning solutions. You will review Python, TensorFlow, PyTorch, and scikit-learn code for correctness and efficiency, and craft clear explanations of model decisions for developers.

You’ll write high-quality ML solutions for modeling, data processing, and deployment, identify edge cases, and help set the quality bar for how AI understands and produces ML code.

Qualifications

• Extensive experience in building and evaluating ML models.
• Ability to explain ML concepts clearly in writing.
• Experience with evaluating AI-generated ML code and datasets.

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

Skills

ML expertise

Strong written communication

Detail-oriented

Independent / async work

Education

Bachelor's/Master's/PhD in CS or ML

Tools

TensorFlow

PyTorch

scikit-learn

Job description

About The Role

What if your machine learning expertise could directly influence how the most advanced AI systems in the world think, reason, and write code? We're looking for experienced ML engineers in Amsterdam and across the Netherlands 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.

Job Details

• Organization: Alignerr
• Type: Hourly Contract
• Location: Remote (Netherlands)
• Commitment: Flexible, project-based

What You'll Do

• 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

Who You Are

• Deeply fluent in machine learning — you know your way around model development, data preprocessing, training pipelines, and deployment
• Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn
• 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

Nice to Have

• 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

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