Software Engineer – Machine Learning (AI Training)

Alignerr Corp.

Greater London

Remote

GBP 83,000 - 152,000

Part time

21 hours ago
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Job summary

Alignerr is seeking an experienced ML engineer in London to evaluate AI-generated machine learning solutions — catching errors, improving quality, and helping frontier models get genuinely better at one of the hardest tasks they do.

This is a fully remote, hourly contract role. Work asynchronously on your own schedule from anywhere in the UK. Review Python-based ML code (TensorFlow, PyTorch, scikit-learn), write clear notes, and help raise the quality bar for AI-driven ML systems across projects.

Qualifications

  • Fluent in machine learning, model development and deployment.
  • Experience with ML frameworks and writing clear technical notes.
  • Ability to work asynchronously with minimal supervision.

Responsibilities

  • Review and evaluate AI-generated ML code for correctness and efficiency.
  • Write high-quality ML solutions for modeling and deployment problems.
  • Explain model architecture decisions clearly for engineers.
  • Identify edge cases and weaknesses in statements and datasets.
  • Help set the quality bar for AI-understanding code.

Skills

ML expertise
Independent/async work
Clear technical writing

Education

CS/ML degree (BSc/MS/PhD)

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 London 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.

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.

  • Organization: Alignerr
  • Type: Hourly Contract
  • Location: Remote (UK-based)
  • 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
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