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Sila Nanotechnologies is a next-generation battery materials company on a mission to power the world's transition to clean energy. They engineer and manufacture breakthrough battery materials that significantly increase energy density while reducing size and weight, enabling smaller, more powerful batteries for consumer devices and electric vehicles.
You will build the intelligence layer for manufacturing operations—systems that help the factory understand what is happening, predict what will happen next, and respond earlier and better. This is a technical builder role focused on hard problems with real operational consequences.
Key responsibilities include:
**Build Manufacturing Intelligence Systems**: Ingest plant telemetry, live data feeds, event logs, quality data, and maintenance history to improve manufacturing prediction and closed-loop response. Reconstruct equipment and process behavior from raw data, surface meaningful deviations, identify process drift, classify fault patterns, and quantify operational risk before failures materialize. Turn raw manufacturing signals into reliable services and applications that improve uptime, yield, and execution speed.
**Develop Models That Matter**: Build and deploy machine learning models for anomaly detection, fault classification, process monitoring, quality prediction, and forecasting. Develop models connecting recipe conditions, process parameters, equipment behavior, and intermediate results to downstream product quality. Build feedforward and feedback models using upstream signals and in-process data. Apply AI models and agentic workflows only where they materially improve engineering execution. Build hybrid solutions combining deterministic engineering logic, statistical methods, optimization, machine learning, and foundation models. Convert model outputs into practical operational logic supporting triage, escalation, and intervention.
**Deploy Into Real Operations**: Design and deploy production-grade APIs, model services, pipelines, and internal tools reliable enough for day-to-day plant use. Build workflows for feature generation, inference, and event detection. Partner closely with Manufacturing, Process Engineering, Controls, Quality, Data Systems, and Software teams. Help define architecture and roadmap for operations intelligence across manufacturing workflows.
You are comfortable working across software, data, engineering logic, and manufacturing systems. You know how to deal with noisy plant data, imperfect systems, and messy failure modes. You have built and shipped systems that changed how an operation runs.
