Machine Learning Engineer
Core
Design, build, and deploy Agentic AI systems that combine time-series modeling, signal processing, and generative AI to power industrial applications for manufacturers.
Role type
Senior IC machine learning engineer (Agentic AI & Industrial AI)
Builds
Agent-based systems leveraging heterogeneous data sources (sensor signals, unstructured text) to deliver operational insights
Domain
Industrial AI / Manufacturing / Time-series forecasting
Deliverable
production ML models
Required skills
time-series modeling, forecasting, anomaly detection, feature engineering, Python, PyTorch, TensorFlow, Scikit-learn, LLMs, embeddings, agent-based architectures, data pipelines, production ML systems, drift detection
Preferred skills
industrial AI, IoT, predictive maintenance, digital twins, knowledge graphs, Databricks, BigQuery, Snowflake, optimization frameworks (Pyomo, Gurobi, OR-Tools), large-scale distributed data systems
Technologies
Pydantic, Langchain, LangGraph, DSPy
Responsibilities
Own the full machine learning lifecycle from problem scoping to production monitoring; Design and build Agentic AI systems integrating time-series modeling and GenAI; Develop ML models for forecasting, anomaly detection, and pattern recognition in industrial sensor data; Integrate classical statistical methods, deep learning, and GenAI techniques; Build scalable data pipelines and ML systems; Collaborate with Product, Engineering, and Algorithm teams; Partner with customers to identify data-driven opportunities; Implement robust evaluation, monitoring, and drift detection systems
Seniority
Senior, hands-on IC