(Jr.) Machine Learning (ML) Developer

Laminar (formerly H2Ok Innovations) • Somerville, MA

1d • $85,000 - $135,000

About The Position

At Laminar (formerly H2Ok Innovations), we're leading the charge in cleantech innovation, reshaping process industrials and manufacturing to drive operational efficiency and sustainability for our world’s most foundational industries. Powered by our Laminar AI Co-pilot models and state-of-the-art sensors, our solutions optimize facility performance across various processes, including process manufacturing, production, water management, energy reduction, and waste minimization. Based at Greentown Labs, North America's premier cleantech innovation community, we're a woman-founded startup backed by renowned investors like Greycroft, Construct Capital, 2048 Ventures, and Flybridge Capital. Our groundbreaking technologies have earned accolades and adoption from industry giants like Unilever, The Coca-Cola Company, ABinBev, and Mitsubishi Electric. We're committed to unlocking untapped data for our customers, empowering them to gain a competitive edge and create Industry 4.0.

Transforming our most foundational sectors of society is hard. Very hard. But we’re building an empire. And empire building is not easy. It’s deeply fulfilling, and you will learn and grow tremendously while driving sustainable impact globally with some of the largest players that make everything we eat, use, and wear. Our culture is to foster extraordinary growth within our teammates. We believe in autonomy, ownership, empowerment, demanding excellence, being mission-driven. We believe in creativity, authenticity, and extraordinary growth. We’re looking for relentless, ambitious, creative, and exceptional people to join our team and build the factory of the future.

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.

Requirements

• 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.

Nice To Haves

• 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

Responsibilities

• 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

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.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: No Education Listed