data engineering

Location: Berkeley, CA, USA Remote: Yes; also open to Bay Area hybrid Willing to relocate: No Technologies: Python, SQL, PySpark, Dagster, AWS, Delta Lake, PyTorch, TensorFlow, TypeScript, React, PostgreSQL, Snowflake Résumé/CV: https://newtrino.ink/resume.pdf LinkedIn: https://www.linkedin.com/in/nishanth-jayram/ Email: [nishanthjayram@gmail.com](mailto:nishanthjayram@gmail.com) Data / ML infrastructure engineer with experience building production-scale ingestion systems, ML pipelines, validation frameworks, and internal engineering tools. Currently at Protege, working on healthcare data ingestion and normalization across large EHR and imaging datasets, with Dagster-based orchestration, schema validation, drift monitoring, and production pipeline reliability improvements. I was previously at Mastercard, where I worked as a machine learning engineer on consumer engagement and merchant-offer forecasting systems: feature pipelines, propensity models, training/inference workflows, Delta Lake migrations, and React/TypeScript dashboards for model performance and production insights. I’m looking for data engineering, ML platform / ML infrastructure, applied ML engineering, or full-stack roles where the work benefits from strong data/ML systems experience and product-minded engineering. Outside of work, I like playing guitar, photographing birds, and watching old episodes of Carl Sagan’s Cosmos.