Senior Machine Learning Engineer
Core
Design and implement machine learning solutions, including GenAI agents and foundation models, to help clients launch innovations in sectors like climate, healthcare, and education.
Role type
Senior Machine Learning Engineer (GenAI & Foundation Models)
Builds
Scalable ML systems, GenAI agents, and production pipelines for diverse client projects.
Domain
Generative AI, Deep Learning, Foundation Models, Climate Tech, Healthcare, EdTech
Deliverable
production ML models
Required skills
Python, ML/DL frameworks (PyTorch, TensorFlow, HuggingFace), GenAI development (prompt engineering, fine-tuning, Agentic RAG, NLQ), data wrangling and visualization, model error analysis, MLOps/LLMOps, AWS environment optimization, client-facing communication, technical documentation, mentorship
Preferred skills
MLOps/LLMOps expertise, AWS Sagemaker/Bedrock, MLFlow, LangFuse, consultancy or startup experience
Technologies
Python, PyTorch, TensorFlow, HuggingFace, LangChain, LangGraph, LlamaIndex, smolagents, strands-agents, AWS, Docker, Kubernetes
Responsibilities
Design and implement complex ML systems using classical ML, deep learning, and foundation models; wrangle, explore, and visualize data; analyze model errors and design strategies to overcome them; deploy, maintain, and upgrade ML models and pipelines; lead client communications by gathering requirements and managing expectations; provide guidance and mentorship to junior ML engineers; drive architectural decisions and contribute to high-level planning; continuously optimize models for performance, scalability, and cost-effectiveness within AWS.
Seniority
Senior, hands-on IC with mentorship responsibilities