Staff Applied ML Engineer
Core
Build intelligence systems for manufacturing operations to predict equipment behavior, detect faults, and optimize production quality.
Role type
Staff Applied ML Engineer (Manufacturing Operations)
Builds
Production-grade APIs, model services, pipelines, and internal tools for plant operations
Domain
Battery materials manufacturing / Industrial IoT / Predictive Maintenance
Deliverable
production ML models | product features
Required skills
Python, scientific computing (pandas, NumPy, SciPy), machine learning libraries (PyTorch, TensorFlow, XGBoost), software services/APIs (FastAPI, Flask, SQL, Spark, Airflow), time-series and sensor data processing, model deployment, systems thinking
Preferred skills
predictive maintenance, process monitoring, fault analysis, multivariate analysis, optimization, hybrid physics and data-driven approaches, LLMs/agentic systems
Technologies
PyTorch, TensorFlow, XGBoost, FastAPI, Flask, SQL, Spark, Airflow, dbt
Responsibilities
Build systems ingesting plant telemetry and event logs to improve manufacturing prediction; Develop ML models for anomaly detection, fault classification, and quality forecasting; Deploy production-grade APIs and workflows for inference and feedback; Partner with engineering and operations teams to define operations intelligence architecture
Seniority
Staff, hands-on IC with strategic scope