We are seeking a Senior AI/Machine Learning Engineer to design, build, and deploy production AI/ML solutions for clients in a consulting environment. The role covers the full ML lifecycle—from framing business problems and training models to deployment, monitoring, and MLOps—with strong emphasis on generative AI and LLMs. You will also act as a trusted technical advisor to stakeholders, mentor teammates, and contribute flexibly across adjacent engineering tasks.
Responsibilities
Own ML solutions end to end, from problem framing and data exploration through training, evaluation, production deployment, and monitoring.
Apply generative AI and LLMs where appropriate, including RAG, embeddings, fine-tuning, and major model APIs.
Establish MLOps best practices: CI/CD for models, experiment tracking, model/drift monitoring, and responsible-AI practices.
Translate ambiguous business problems into well-scoped solutions and serve as a trusted technical advisor to client stakeholders.
Mentor teammates and collaborate across multi-disciplinary teams; contribute flexibly to adjacent engineering, data, or DevOps work.
Requirements
4+ years building, training, and deploying ML models in production.
Strong modeling fundamentals: feature engineering, model selection, bias/variance, regularization, overfitting, and rigorous evaluation.
Deep learning fundamentals with hands-on PyTorch or TensorFlow experience.
Databricks is the Data and AI company that created the Lakehouse architecture, providing a unified platform for data engineering, SQL analytics, machine learning, and AI on open data formats. It was founded by the creators of Apache Spark.