What you’ll do
● Build and validate ML/AI models on semiconductor process, equipment, and manufacturing data.
● Work on yield optimization, process control (APC / SPC), fault detection and classification (FDC), and anomaly detection.
● Handle high-volume, high-dimensional sensor / trace and metrology data; build robust pipelines.
● Turn manufacturing problems into well-scoped modeling problems with the technical team.
● Design rigorous validation and monitoring for models running in an industrial setting.
● Partner with the semiconductor technical lead and engineering to move models toward production.
● Ensure traceability, reproducibility, and governance of models and data.
What we’re looking for
● Strong experience applying AI/ML to semiconductor or comparable industrial / manufacturing data.
● Hands-on with process control, manufacturing analytics, yield optimization, or fault / anomaly detection.
● Comfort with high-dimensional time-series / sensor / metrology data and its noise.
● Solid statistics and signal-processing fundamentals.
● Discipline around validation, reproducibility, and documentation.
Technical skill stack
The tools and technologies you should be strong in. We don’t expect every single item — depth in the core stack matters most.
● Programming: Python (expert) and SQL; MATLAB a plus; some C / C++ helpful
● ML & deep learning: scikit-learn, PyTorch, TensorFlow, XGBoost / LightGBM
● Data & statistics: pandas, NumPy, SciPy, statsmodels; multivariate analysis (PCA / PLS)
● Time-series & signal: signal processing, FFT / wavelets, anomaly detection; tsfresh, sktime
● Industrial statistics: SPC, design of experiments (DOE), capability analysis, Bayesian methods
● Semiconductor domain: FDC / APC / SPC, virtual metrology, run-to-run control, yield analysis
● Fab data systems: MES, SECS / GEM, and equipment / metrology / trace data
● Data platforms: Spark, Kafka; time-series stores (InfluxDB / TimescaleDB); PostgreSQL
● MLOps: MLflow, Docker; pipelines with Airflow or Prefect; model deployment
● Cloud & edge: AWS, GCP, or Azure; industrial / edge deployment a plus
eSora Labs is for builders, thinkers, designers, engineers, and domain experts who want to work across AI, software, design, healthcare, semiconductor, aerospace, and regulated technology.