Machine Learning (ML) Applications Engineer- Chemical/Process EngineeringLaminar (formerly H2Ok Innovations) • Somerville, Massachusetts, United States
Machine Learning (ML) Applications Engineer- Chemical/Process Engineering
Laminar (formerly H2Ok Innovations)
- Somerville, Massachusetts, United States
- Somerville, Massachusetts, United States
About
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
About You
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 (NumPy, Pandas), MATLAB, or R; experience with ML libraries (Scikit‑Learn, TensorFlow, 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
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 401(k) 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 How We Think
Learn about our startup journey: Our Journey How we’re combating climate change: AI‑Powered Climate Tech A customer story: Ben & Jerry’s uses Laminar’s precision automation to cut time & water usage
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
Phone screen with Laminar Head of Ops or Recruiter (15‑20 minutes) Intro call with Hiring Manager (30 minutes) 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 so we can share with any team members who could not join the interview and/or with Founders for the Founders Interview. Finalists 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.
Laminar is committed to building a diverse and inclusive team. We strongly encourage women and non‑binary folks who may feel unsure if they’re a perfect fit 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 may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Opportunity for Growth. Seniority level: Not Applicable Employment type: Full‑time Job function: Engineering and Information Technology Industries: Transportation, Logistics, Supply Chain and Storage #J-18808-Ljbffr
Languages
- English
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