(Jr) Machine Learning (ML) Developer

The Role

As our company grows and scales, we are excited for a ML Developer to join the team! We are looking for ambitious, hard-working recent graduates who want to be at the forefront of bringing AI to fluid & process manufacturing . 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

• 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.

Preferred:

• Chemical engineering, process engineering, or manufacturing domain knowledge (highly valued)
• Experience with cloud environments (AWS, GCP) and/or Databricks
• Familiarity with spectral data, time-series modeling, or sensor-driven ML
• Familiarity with Bayesian modeling and probabilistic reasoning
• Experience building real products (ideally utilizing machine learning) and practicing user-centric design

Benefits

• Direct impact on product and culture.
• Comprehensive benefits package including Medical, Dental, Vision, Life Insurance, Disability, Transportation benefit, Health and Wellness benefit, and more.
• 401k plan with employer matching
• Equity
• Competitive salary and bonus opportunities.
• Dynamic and inclusive work environment.
• Opportunities for growth and professional development.
• Access to Greentown Labs' extensive network of cleantech startups.
• Transportation benefit for your commute
• A team that celebrates together from rooftop lunches, ping pong matches, Lunch & Learns, and regular team events

Learn How We Think

• Learn about our startup journey: Our Journey
• How we're combating climate change: AI-Powered Climate Tech
• A customer story: Unilever uses Laminar precision automation to cut time & water usage