Machine Learning Engineer Talent Network

Workbolt; United States; Remote; USD 96,000 - 344,000; Full time

Benefits offered by this job

Competitive project-based pay

Fully remote opportunities

Access to future ML projects

Job summary

Workbolt AI is seeking a machine-learning engineer to join its Talent Network for flexible, contract-based opportunities with AI labs and tech companies. This open application means you may be considered for future projects based on your experience and availability.

Engagements vary in scope and may be remote; typical commitments are 15–30 hours per week while active, with compensation discussed per engagement and no guaranteed minimum.

Qualifications

• Open application for future project-based contracts.
• Experience in machine-learning engineering.
• Remote opportunities are common in this network.

Responsibilities

• Design realistic ML engineering tasks involving data preparation, feature engineering, model selection, training, evaluation, deployment, monitoring, and reproducibility.
• Evaluate AI-generated ML code, experiments, and explanations for correctness, data leakage, and production readiness.
• Develop evaluation criteria, datasets, test cases, and exemplar solutions for professional ML work.
• Provide precise technical feedback identifying modeling errors, leakage, or deployment risks.
• Work independently within project instructions, document assumptions and dependencies, and meet deadlines.

Job description

About the role

About Workbolt AI’s Talent Network Join Workbolt AI’s Machine Learning Engineer Talent Network to be considered for flexible contract opportunities with AI labs and technology companies seeking experienced machine learning engineering professionals. This is an open application for future projects—not a guarantee of immediate work. Opportunities are matched on a rolling basis according to your experience, technical expertise, availability, and project requirements. What You May Work On Members of the network may support projects that train, test, and evaluate advanced AI systems using real-world engineering expertise. Assignments may include creating realistic technical tasks and deliverables; reviewing AI-generated code, architectures, debugging approaches, and documentation; developing scoring criteria, test cases, or reference solutions; and providing detailed feedback on correctness, maintainability, security, performance, and production relevance. Focus areas may include machine-learning model development, Python, PyTorch or TensorFlow, data pipelines, experiment design, model evaluation, deployment, monitoring, and MLOps. Project Details Projects vary in scope, duration, and weekly commitment. Many engagements are structured for flexible remote participation and may require approximately 15–30 hours per week while active. Specific schedules, deliverables, technology stacks, timelines, and compensation terms will be shared before you accept an assignment. Projects may be extended, shortened, or concluded as business needs and performance requirements change. Contract Information Talent Network members participate as independent contractors on project-based engagements. Joining the network does not create an employment relationship or guarantee a minimum amount of work. Experts must not use or disclose confidential, proprietary, material non-public, or restricted information, datasets, models, or source code belonging to any current or former employer, client, or institution. Workbolt AI considers qualified applicants without regard to legally protected characteristics and supports reasonable accommodations where applicable.

Responsibilities

• Design realistic machine-learning engineering tasks involving data preparation, feature engineering, model selection, training, evaluation, deployment, monitoring, and reproducibility.
• Evaluate AI-generated ML code, experiments, and explanations for mathematical and statistical soundness, correctness, data leakage, reproducibility, efficiency, robustness, and production readiness.
• Develop evaluation criteria, datasets, test cases, scoring rubrics, reference implementations, and exemplar solutions that define professional-quality machine-learning engineering work.
• Provide precise technical feedback identifying modeling errors, invalid metrics, leakage, weak baselines, flawed experimental design, deployment risks, monitoring gaps, or unsupported conclusions.
• Work independently within project instructions and quality standards, document assumptions, data constraints, and dependencies, incorporate reviewer feedback, meet deadlines, and communicate risks.

Benefits

• Competitive project-based compensation of $70–$250 per hour, depending on the engagement and your experience.
• Flexible, fully remote contract opportunities designed to accommodate independent schedules.
• Access to future machine-learning engineering and AI‑evaluation projects matched to your expertise, interests, and availability.

Pay

$70–$250/hr

Workbolt is an AI-training platform from Ocular AI (Y Combinator W24, San Francisco). Talent-network roles are open applications for future projects;