Senior Machine Learning Engineer

Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field. 5+ years of experience in Machine Learning Engineering or a similar role. Proven experience with large-scale data preprocessing, LLM/model training, and fine-tuning. Experience with distributed training (PyTorch Distributed, DeepSpeed, Ray, Hugging Face Accelerate). Experience with GPU/TPU optimization, memory management for large language models. Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy). Strong understanding of various machine learning algorithms, Large Language Models, and deep learning architectures. Experience with cloud platforms (e.g., GCP, AWS) and distributed computing frameworks (e.g., Spark) is a plus. Familiarity with MLOps practices and tools. Excellent problem-solving and analytical skills. Strong communication and collaboration abilities. Ability to work independently and as part of a team.

Data Preprocessing: Clean, transform, and prepare large, complex healthcare datasets. Model Training & Fine-Tuning: Design, train, and fine-tune LLMs on healthcare data. Model Evaluation & Optimization: Evaluate model performance and implement optimization strategies. Pipeline Development: Develop and maintain data and ML pipelines. Collaboration: Work with data scientists, clinicians, and software engineers. Research & Development: Stay updated on ML and healthcare AI advancements. Documentation: Maintain documentation of models, data pipelines, and results.