(Jr.) Machine Learning (ML) Developer
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.
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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
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Design and run experiments to evaluate and select machine learning models that are generalizable, accurate, and robust to day-to-day process variability
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Work with spectral and multi-modal sensor data, building preprocessing and feature extraction pipelines that can derive insights from noisy, real-world sensors
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Support model reliability by developing monitoring (and correction systems, when applicable) for model drift, sensor drift, and process anomalies
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Develop performant ML infrastructure and tooling in collaboration with ML/Data Scientists and software team members
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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
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Proficient in at least one Python ML framework (PyTorch, JAX, TensorFlow)
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Fluent with Python packages for numeric computing and data workflows (e.g. NumPy, Polars, Pandas, scikit-learn)
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An engineer who favors clean, testable code and has a proven track record of delivering high-quality work on a timeline
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An executor who thrives with direction and can independently complete technical project objectives
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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.
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Chemical engineering, process engineering, or manufacturing domain knowledge (highly valued)
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Experience with cloud environments (AWS, GCP) and/or Databricks
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Familiarity with spectral data, time-series modeling, or sensor-driven ML
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Familiarity with Bayesian modeling and probabilistic reasoning
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Experience building real products (ideally utilizing machine learning) and practicing user-centric design
- 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.
- Learn about our startup journey: Our Journey
- How we're combating climate change: AI-Powered Climate Tech
Why Laminar (formerly H2Ok Innovations)?
Impact: Work on cutting-edge AI and sensor tech that’s already transforming how factories use water, energy, and chemicals. Join a tight-knit, ambitious team where your contributions can reshape the industry.
Growth: Join a fast-growing startup where you’ll have the opportunity to shape our content strategy. We value fostering extraordinary growth in our teammates.
Innovative Culture: Work in a high-performance environment that values empowerment, creativity, ownership, autonomy, innovation, excellence, passion, and continuous growth.
Sustainability Focus: Play a key role in promoting sustainability and Industry 4.0 advancements in manufacturing.
Build the intelligence layer powering the next generation of industrial efficiency – with a team that moves fast and delivers real impact.
Our Interview Process
1. Phone screen with Laminar Head of Ops or Recruiter (15-20 minutes)
2. Intro call with Hiring Manager (30 minutes)
3. On-site interview, including short tour of GTL, overview of tech, and interview/presentation with the Hiring Manager and a few team members. Depending on the role, a skills exercise that should take no longer than an hour to prep, would be sent ahead of time. We record your skills exercise to share with any team members who could not join the interview and/or with Founder's ahead of their Founder's Interview. If you are not local, we can conduct this virtually.
4. Finalists for Full-Time positions will have a Founder’s Interview in-person
Final steps:
Two professional references are requested, ideally one from your current organization and one who served as your Manager
If an Offer Letter is extended, a Background check is conducted
A recent study from LinkedIn showed that most women apply to jobs only when they meet 100% of the requirements, whereas men will hit the apply button if they hit 60%. Laminar (formerly H2Ok) is committed to building a diverse and inclusive team. So, to the women and nonbinary folks out there feeling unsure if you're a perfect fit, we strongly encourage you to apply! If you're ready to play a key role in scaling a game-changing company that’s transforming the industrial sector and advancing sustainability, we want to hear from you!
* We recently updated our domain to runlaminar.com. Please ensure you add the runlaminar.com domain to your safe senders list to ensure you receive our communications.
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