Machine Learning Engineer

Machine Learning Engineers

Compensation

Bonus

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.
  

Eligibility

• 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.
  

• You will be engaged as an independent contractor.
• This is a fully remote role that can be completed on your own schedule.
• Projects can be extended, shortened, or concluded early depending on needs and performance.
• Your work will not involve access to confidential or proprietary information from any employer, client, or institution.
• You will work on projects that focus on training and enhancing AI systems. You will be paid competitively, collaborate with leading researchers, and help shape the next generation of AI systems in your area of expertise.