Software Engineer – Machine Learning (AI Training)

Alignerr Corp.; New York (NY); Remote; USD 83,000 - 165,000; Part time

Benefits offered by this job

Remote work

Async schedule

Job summary

Alignerr is seeking an experienced ML engineer for an hourly contract role based remotely in the US. You will evaluate AI-generated ML code, improve model quality, and help frontier AI models become more reliable. The role emphasizes independent, asynchronous work with flexible scheduling and high-impact outcomes.

You will apply TensorFlow, PyTorch, and scikit-learn to a range of modeling, data processing, and deployment tasks, while clearly communicating decisions and findings in writing.

Qualifications

• Deep ML expertise across model development, evaluation, and deployment.
• Proven ability to explain complex ML concepts clearly in writing.
• Experience working asynchronously and independently on ML projects.
• Strong problem-solving and attention to detail.

Responsibilities

• Review and evaluate AI-generated ML code for correctness and efficiency.
• Develop high-quality ML solutions for modeling, data processing, and deployment.
• Craft clear explanations of model architecture and code decisions.
• Identify edge cases and weaknesses in data, prompts, or AI outputs.
• Help raise the quality bar for AI-understood ML code.

Skills

Machine learning

Written communication

Independent work

Attention to detail

Education

Bachelor's/Master's/PhD in CS/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 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.

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 (US-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