Negotiable
Undetermined
Remote
United Kingdom
Summary: The role involves joining Mercor’s Machine Learning Engineer Network as a part-time or project-based position, focusing on machine learning model development and optimization. Candidates will work remotely, contributing to AI-driven projects and collaborating with engineering teams. An initial AI interview is required for eligibility in relevant job listings. The position offers flexible hours ranging from 10 to 40 hours per week.
Key Responsibilities:
- Join Mercor’s Machine Learning Engineer Network to be matched with companies hiring for ML-focused roles
- Contribute to machine learning model development and applied AI system optimization
- Work with Python and ML frameworks such as PyTorch or TensorFlow
- Support model deployment and MLOps workflows
- Participate in AI-driven opportunity matching for full-time, part-time, or project-based roles
- Complete an initial AI interview to become eligible for relevant listings aligned with experience
Key Skills:
- Professional experience in machine learning engineering
- Proficiency in Python and ML frameworks such as PyTorch or TensorFlow
- Experience with model deployment and MLOps workflows
- Strong understanding of applied AI system optimization
- Ability to collaborate with AI labs and cross-functional engineering teams
- Willingness to complete an AI interview for opportunity matching
Salary (Rate): £250.00/hr
City: undetermined
Country: United Kingdom
Working Arrangements: remote
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
Position: Join Expert Network: Machine Learning Engineer
Type: Part-time / Project-based
Compensation: $70–$250 per hour
Location: Remote
Commitment: 10–40 hours/week
Role Responsibilities
- Join Mercor’s Machine Learning Engineer Network to be matched with companies hiring for ML-focused roles
- Contribute to machine learning model development and applied AI system optimization
- Work with Python and ML frameworks such as PyTorch or TensorFlow
- Support model deployment and MLOps workflows
- Participate in AI-driven opportunity matching for full-time, part-time, or project-based roles
- Complete an initial AI interview to become eligible for relevant listings aligned with experience
Requirements
- Professional experience in machine learning engineering
- Proficiency in Python and ML frameworks such as PyTorch or TensorFlow
- Experience with model deployment and MLOps workflows
- Strong understanding of applied AI system optimization
- Ability to collaborate with AI labs and cross-functional engineering teams
- Willingness to complete an AI interview for opportunity matching
Application Process (Takes 20 Mins)
- Upload resume
- Interview (15 min)
- Submit form