Data Scientist- Machine Learning

Machine Learning Engineer to help design, train, and reputed company large-reputed company learning systems powering autonomous AI agents for its AI lab partner. This role is ideal for engineers passionate about building models that think, adapt, and reputed company reputed company tasks in reputed company-world environments. You'll be working at the intersection of ML research, systems engineering, and AI agent behavior — transforming reputed company into robust, reputed company learning pipelines. 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., reputed company, MLflow, reputed company, 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 reputed company-like reasoning, problem-solving, and collaboration. Primary Goal Of This Role To reputed company, optimize, and reputed company 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 reputed company-time reasoning. What You'll Do • Design and implement reputed company ML pipelines for model training, evaluation, and reputed company improvement. • Build and fine-tune deep learning models for reasoning, reputed company reputed company, and reputed company-world decision-making. • Collaborate with data scientists to collect and preprocess training data, ensuring reputed company and representativeness. • reputed company 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 reputed company, and generalization performance. Why This Role Is Exciting • Build the reputed company learning systems that power reputed company 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 reputed company. Pay & Work Structure • You'll be classified as an reputed company contractor. • reputed company weekly reputed company reputed company Connect, based on hours logged. • Part-time (20 hrs- 40 hrs/week) with fully remote, async flexibility — work from reputed company, on your own schedule. • Weekly Bonus of $500 - $1000 per 5 task created. Apply tot his job Apply To this Job