About Us

We are Sila a next-generation battery materials company. Our mission is to power the worlds transition to clean energy. To create this future our team is building a better lithium-ion battery from the inside out today. We engineer and manufacture ground-breaking battery materials that significantly increase the energy density of batteries while reducing their size and weight. The result Smaller more powerful batteries that can unlock innovation in consumer devices and accelerate the mass adoption of electric cars to eliminate our dependence on fossil fuels. Were tackling one of the biggest challenges of our time every day and together were redefining whats possible. Are you ready to be a part of a team committed to changing the world

Who You Are

You are excited to build the intelligence layer for manufacturing operations: systems that help the factory understand what is happening predict what is likely to happen next and respond earlier and better as a result.

You are a strong technical builder who likes hard problems with real operational consequences. You can take an ambiguous manufacturing problem and turn it into a working system that engineers and operations teams actually use.

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 do not stop at visibility. You build systems that drive action.

We are looking for someone who has built and shipped systems that changed how an operation runs.

Build Manufacturing Intelligence Systems

• 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
• 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 forecasting and related manufacturing use cases
• Develop models that connect recipe conditions process parameters equipment behavior and intermediate process results to downstream product quality and performance outcomes
• Build feedforward and feedback models that use upstream signals in-process data and downstream results to improve decisions during execution
• Apply AI models and agentic workflows only where they materially improve engineering execution diagnosis knowledge retrieval or workflow automation
• Build hybrid solutions that combine deterministic engineering logic statistical methods optimization machine learning and foundation models where each adds the most value
• Convert model outputs into practical operational logic that supports triage escalation intervention and action

Deploy Into Real Operations

• Design and deploy production-grade APIs model services pipelines and internal tools that are reliable enough for day-to-day plant use
• Build workflows for feature generation inference event detection and feedback into operational systems
• Partner closely with Manufacturing Process Engineering Controls Quality Data Systems and Software teams to ensure outputs are technically sound and tied to real plant actions
• Help define the architecture and roadmap for operations intelligence across manufacturing and adjacent factory workflows

Qualifications

• Bachelors Masters 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
• Experience training validating and deploying custom models for prediction classification anomaly detection forecasting optimization or control-related use cases
• Strong systems thinking and the ability to translate ambiguous plant problems into robust technical solutions
• Experience taking technical systems from concept to deployment with measurable real-world impact
• Strong written and verbal communication skills and the ability to work effectively across technical and operational teams

Preferred Qualifications

• 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 with sequence modeling multivariate analysis optimization simulation or hybrid physics and data-driven approaches
• 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

The starting base pay for this role is between $151000 and $177500 at the time of posting. The actual base pay depends on many factors such as education experience and skills. Base pay is only one part of Silas competitive Total Rewards package that can include benefits perks equity. The base pay range is subject to change and may be modified in the future. #LI-RS1 #LI-Onsite

Working at Sila

We believe that building a diverse team at Sila helps us amplify our individual talents. We are an equal opportunity employer and committed to creating an inclusive environment where good ideas are free to come from anyone. We are proud to celebrate diversity and 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.