Remote Machine Learning Engineer - India - AI Trainer ($14-$14 per hour)

### You’re a great fit if you : - Have a strong background in

• machine learning, deep learning, or reinforcement learning
• . - Are proficient in
• Python
• and familiar with frameworks such as
• PyTorch, TensorFlow, or JAX
• . - Understand
• training infrastructure
• , including distributed training, GPUs / TPUs, and data pipeline optimization. - Can implement
• end-to-end ML systems
• , from preprocessing and feature extraction to training, evaluation, and deployment. - Are comfortable with
• MLOps tools
• (e.g., Weights & Biases, MLflow, Docker, Kubernetes, or Airflow). - Have experience designing
• custom architectures or adapting LLMs, diffusion models, or transformer-based systems
• . - Think critically about
• model performance, generalization, and bias
• , and can measure results through data-driven experimentation. - Are curious about
• AI agents
• and how models can simulate human-like reasoning, problem-solving, and collaboration. ### Primary Goal of This Role To develop, optimize, and deploy machine learning systems that enhance agent performance, learning efficiency, and adaptability. You’ll design model architectures, training workflows, and evaluation pipelines that push the frontier of autonomous intelligence and real-time reasoning. ### What You’ll Do - 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
• . - Maintain
• model reproducibility and version control
• , integrating with experiment tracking systems. - Contribute to
• cross-functional research efforts
• to improve learning strategies, fine-tuning methods, and generalization performance. ### Why This Role Is Exciting - Build the
• core learning systems
• that power next-generation AI agents. - Combine
• ML research, engineering, and systems-level optimization
• in one role. - Work on
• uncharted challenges
• , designing models that can reason, plan, and adapt autonomously. - Collaborate with a world-class AI team redefining how autonomous systems learn and evolve. ### Pay & Work Structure - You’ll be classified as an
• hourly contractor
• to Mercor. -
• Paid weekly
• via Stripe Connect, based on hours logged. -
• Part-time (20 hrs- 40 hrs / week)
• with fully remote, async flexibility — work from anywhere, on your own schedule. - Weekly Bonus of $500 - $1000 per 5 task created.