Machine Learning Engineer

Responsibilities

• Design and develop machine learning and deep learning models
• Build scalable data pipelines for training, evaluation, and inference
• Develop and productionize AI systems as APIs and services
• Design and implement RAG pipelines for knowledge-driven applications
• Work with LLM frameworks such as LangChain and LlamaIndex
• Build embedding pipelines and integrate vector search systems
• Optimize model performance, latency, and scalability
• Collaborate with backend teams to integrate AI systems into products

Requirements

• Strong proficiency in Python and machine learning libraries
• Solid understanding of machine learning and deep learning fundamentals
• Experience building and deploying ML models in production environments
• Experience with data preprocessing, feature engineering, and model evaluation
• Experience in productionizing ML systems including model APIs and inference systems
• Understanding of scalable ML architectures and data pipelines
• Experience with LangChain, LlamaIndex, or similar LLM frameworks
• Understanding of RAG (Retrieval-Augmented Generation) pipelines
• Experience with embeddings, semantic search, and vector databases

Preferred Qualifications

• Experience with generative models, graph-based models, or diffusion models
• Exposure to life sciences, cheminformatics, or scientific data
• Experience with Docker, Kubernetes, and deployment pipelines
• Experience working on AI-first or data platform products