Junior Machine Learning Developer

Salary Range: 89000 to 141000 (Currency: USD) (Pay period: per-year-salary)

Machines learned to understand language. We’re teaching them to understand matter.

Forty percent of global manufacturing happens through physical and chemical processes inside pipes, tanks, and reactors. Despite decades of industrial automation, much of what happens inside them remains remarkably invisible. Manufacturing is the most ubiquitous and foundational sector in global economy, yet the way factories are fundamentally run have used the same control philosophies, manual operations, and legacy software for the past 60 years.

Laminar deploys state-of-the-art patented sensors and edge hardware directly into live production environments, generating data that didn’t previously exist to build foundation models deployed in factory floors that understand chemistry, composition, quality, and material state in real time. We use that understanding to run autonomy and rethink how things are made.

The last generation of industrial automation taught machines to execute instructions reliably. The next will teach them to understand the processes they control and run autonomously, adaptively, and agentically: higher quality, safety, more efficiently, sustainably, and productively. 

That future is already taking shape. Today, Laminar works with 7 of the world’s 10 largest food and beverage manufacturers and operates across hundreds of factories globally across six continents. Our systems have materially reduced waste, cut manufacturing downtime, saved water, chemicals, energy, and helped prevent safety and quality failures. Our technology has gained international recognition, from being selected as a 2026 World Economic Forum Technology Pioneer, Gold 2026 Edison Award, Unilever Startup of the Year, to Innovator Awards by both Coca-Cola and AB InBev, and more.

We are backed by tier-one investors in physical AI to make intelligent, self-improving production the new standard for industry.

Join us to build what makes matter intelligible, and the intelligible controllable.

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