(Jr.) Machine Learning (ML) Developer

Job Description

 As a ML Developer, you will own the development and refinement of Laminar’s machine learning models – the heart of our process optimization technology. Your work will affect all of Laminar’s key process optimization models across domains including (but not limited to): CIP (clean-in-place), product changeovers, material identification, and emerging use-cases.

You’ll work closely with ML/Data Scientists to bring cutting-edge models all the way from prototype to production. This entails scaling up model training methodologies, crafting experiments, and running ablation studies across a wide and diverse range of domains, all with the goals of increasing model accuracy and reliability. Your work will be instrumental to hyper-scaling Laminar’s solutions and unlocking key markets through enabling new use-cases.

What You Will Do

• Build machine learning models that usher in the next generation of data-driven, fluid-based industrial processes powered by Laminar’s proprietary spectral sensors and software platform
• Design and run experiments to evaluate and select machine learning models that are generalizable, accurate, and robust to day-to-day process variability
• Work with spectral and multi-modal sensor data, building preprocessing and feature extraction pipelines that can derive insights from noisy, real-world sensors
• Support model reliability by developing monitoring (and correction systems, when applicable) for model drift, sensor drift, and process anomalies
• Develop performant ML infrastructure and tooling in collaboration with ML/Data Scientists and software team members
• Work across problem domains including chemometrics, hybrid modeling, and self-supervised learning. Modeling tasks include distribution modeling, drift and anomaly detections, similarity analyses, and continuous calibration
  
  
  
  

About You
Required:

• Proficient in at least one Python ML framework (PyTorch, JAX, TensorFlow)
• Fluent with Python packages for numeric computing and data workflows (e.g. NumPy, Polars, Pandas, scikit-learn)
• An engineer who favors clean, testable code and has a proven track record of delivering high-quality work on a timeline
• An executor who thrives with direction and can independently complete technical project objectives
• Someone detail-oriented who has a natural curiosity about data. You are enthusiastic to test out hypotheses, understand in detail how our models work, and run physical experiments to improve our modeling capabilities.

Are you interested in this position?

Apply by clicking on the “Apply Now” button below!

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