Machine Learning; ML Applications Engineer- Chemical/Process Engineering
Listed on 2025-12-01
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Engineering
AI Engineer
Machine Learning (ML) Applications Engineer – Chemical/Process Engineering
4 weeks ago – Be among the first 25 applicants.
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Laminar (Formerly H2Ok Innovations) provided pay range
This range is provided by Laminar (Formerly H2
Ok Innovations). Your actual pay will be based on your skills and experience – talk with your recruiter to learn more.
$82,000.00/yr – $/yr
At Laminar, we’re leading the charge in cleantech innovation, reshaping process industrials and manufacturing to drive operational efficiency and sustainability. Powered by our 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, Nort 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 technologies have earned accolades and adoption from industry giants such as 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 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 fosters extraordinary growth within our teammates. We believe in autonomy, ownership, empowerment, demanding excellence, and 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 an ML Applications Engineer to join the team! As an ML Applications Engineer, you’ll lead the charge in bringing our optimization models to life — starting with Clean‑In‑Place (CIP) processes and expanding into other critical operations.
You’ll work directly with customer process teams, dig into real production data, fine‑tune our machine learning models, and present to customers so they deliver measurable results. Your work will directly drive customer success, renewals, and expansion — making you a key player in scaling our impact worldwide.
What You Will Do- Own the post‑sales deployment of Laminar’s optimization models for CIP and other processes
- Partner with customer teams to understand their operations, align on success metrics, and ensure models deliver in their environment
- Tune and improve ML models to unlock measurable water, energy, and time savings
- Turn process and sensor data into clear, compelling stories that drive action
- Lead customer presentations and workshops, communicating results to both technical and non‑technical audiences, and guiding them to understand the data and our tool
- Collaborate with data science, software, and product teams to continually improve performance and reliability
- Travel on‑site to customer facilities (10–20%) to gain firsthand process understanding and ensure successful deployments
- Strong preference for a background in chemical engineering or chemistry. We will also consider process or mechanical engineering background.
- Strong data analysis skills
- Skilled in Python (Num Py, Pandas), MATLAB, or R; experience with ML libraries (Scikit‑Learn, Tensor Flow, PyTorch, JAX) is a plus
- Experienced in working with sensor and time‑series data
- Confident communicator and presenter, comfortable leading discussions with customer stakeholders and creating compelling data visualizations
- Able to work in industrial plant environments, lab settings, and collaborative cross‑functional teams
- Startup mindset – adaptable, hands‑on, and focused on delivering impact
- Bonus: experience in manufacturing sectors like chemicals, food & beverage, brewing, dairy, or pharmaceuticals
- D…
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