At Mercor, we seek a skilled Machine Learning Engineer for a contract role focusing on designing and implementing scalable ML pipelines, building deep learning models, and collaborating with data scientists.
Key Highlights
Technical Skills Required
Benefits & Perks
Job Description
About The Job
Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.
Position: Machine Learning Engineer
Type: Contract
Compensation: $14/hour
Location: Remote
Role Responsibilities
- Design and implement scalable ML pipelines for model training, evaluation, and continuous improvement.
- Build and fine-tune deep learning models for reasoning, code generation, and real-world decision-making.
- Collaborate with data scientists to collect and preprocess training data, ensuring quality and representativeness.
- Develop benchmarking tools that test models across reasoning, accuracy, and speed dimensions.
- Implement reinforcement learning loops and self-improvement mechanisms for agent training.
- Work with systems engineers to optimize inference speed, memory efficiency, and hardware utilization.
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Must-Have
- Strong background in machine learning, deep learning, or reinforcement learning.
- Proficiency in Python and familiarity with PyTorch, TensorFlow, or JAX.
- Understanding of training infrastructure, including distributed training, GPUs/TPUs, and data pipeline optimization.
- Experience with end-to-end ML systems, from preprocessing and feature extraction to training, evaluation, and deployment.
- Comfort with MLOps tools (e.g., Weights & Biases, MLflow, Docker, Kubernetes, or Airflow).
- Experience designing custom architectures or adapting LLMs, diffusion models, or transformer-based systems.
- Weekly Bonus of $500 - $1000 per 5 tasks created.
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- Upload resume
- AI interview based on your resume
- Submit form
- For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome/welcome
- For any help or support, reach out to: support@mercor.com
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