Staff Applied ML Engineer (AI)

TL;DR

Staff Applied ML Engineer (AI): Building manufacturing intelligence systems that ingest plant telemetry, live data feeds, and operational context to improve manufacturing prediction and closed-loop response with an accent on reconstructing equipment and process behavior from raw data. Focus on developing models that connect recipe conditions, process parameters, and equipment behavior to downstream product quality and performance outcomes.

Location: Alameda, CA

Salary: $151,000 - $177,500

Company

Sila is a next-generation battery materials company powering the world’s transition to clean energy by building better lithium-ion batteries.

What you will do

• Build in-house production systems that ingest plant telemetry, live data feeds, event logs, quality data, maintenance history, and operational context to improve manufacturing prediction and closed-loop response.
• Reconstruct equipment and process behavior from raw data and surface meaningful deviations between expected and actual execution.
• Develop systems that identify process drift, classify fault patterns, and quantify operational risk before failures, downtime, or quality losses fully materialize.
• Build and deploy machine learning models for anomaly detection, fault classification, process monitoring, quality prediction, forecasting, and related manufacturing use cases.
• Design and deploy production-grade APIs, model services, pipelines, and internal tools that are reliable enough for day-to-day plant use.
• Help define the architecture and roadmap for operations intelligence across manufacturing and adjacent factory workflows.

Requirements

• Bachelor’s, Master’s, or PhD in Engineering, Computer Science, Operations Research, Industrial Engineering, or a related technical field.
• Strong programming skills in Python and experience building production-quality software, internal applications, or data products beyond notebooks and dashboards.
• Strong experience with scientific computing and machine learning libraries such as pandas, NumPy, SciPy, scikit-learn, statsmodels, PyTorch, TensorFlow, XGBoost, or equivalent tools.
• Experience building and deploying software services, APIs, data pipelines, or internal platforms using tools such as FastAPI, Flask, SQL, Spark, Airflow, dbt, or similar technologies.
• Experience working with time-series, sensor, event, equipment, MES, historian, quality, or other industrial data.
• Strong systems thinking and the ability to translate ambiguous plant problems into robust technical solutions.

Nice to have

• Experience building models that connect process conditions or recipe parameters to downstream quality or product performance outcomes.
• Experience with predictive maintenance, process monitoring, fault analysis, quality prediction, or root-cause analysis in industrial settings.
• Familiarity with MES, historians, plant systems architecture, or controls-adjacent environments.
• Experience using modern AI workflows, including LLMs or agentic systems, in practical engineering or operational contexts.
• Manufacturing experience is a plus, but we welcome candidates from adjacent operational domains with strong applied modeling and deployment experience.

Culture & Benefits

• Competitive Total Rewards package that can include benefits, perks, equity.
• Inclusive environment where good ideas are free to come from anyone.
• Committed to creating an inclusive environment where all qualified applicants are considered for employment without regard to gender, race, sexual orientation, religion, age, disability, national origin, or any other status protected by law.