Machine Learning (ML) Applications Engineer- Chemical/Process Engineering- Hiring multiple

Somerville, MA

{"min":82000,"max":101000,"currency":"USD","interval":"per-year-salary"}

Our pay ranges are established per Pave Compensation Software. We’re also proud to offer equity in our fast-growing startup and one of the most comprehensive benefits packages among startups at our stage. Laminar pays 100% of the individual health insurance premium for HMO medical, vision, and dental, offers flexible PTO, a $90/month transportation benefit, a $65/month health and wellness benefit, FSA, 12 company-paid holidays, an employer-matching 401(k) (unheard of at this stage!), and Greentown Labs membership, among other valuable resources. (*subject to change)

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.

As our company grows and scales, we are excited for a 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 H2Ok’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.
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 How We Think

Learn about our startup journey: Our Journey
How we're combating climate change: AI-Powered Climate Tech

Why Laminar?

There are many easier places to work on AI. Laminar is for people who want the hardest version of their discipline. Models here must survive contact with physics. Hardware must survive years of continuous industrial operation. Software must integrate with machinery built decades ago. Everything we build ultimately has to work on a factory floor.

We believe exceptional people should be given exceptional amounts of ownership. At Laminar, you will have the context to form your own view, the permission to challenge ours, and the resources to pursue the right answers, whatever technical or organizational boundaries stand in the way. There are few layers between identifying something important and changing it.

We’re fortunate to work with a small polymathic team of hardware and software engineers, chemists, AI researchers, factory operators, and go-to-market wizards who are unusually capable, curious, rigorous, ambitious, and low-ego. If that sounds like you, we’d love to meet you.

Our Interview Process

1. Phone screen with Laminar HR/Recruiter (15-20 minutes)

2. Intro call with Hiring Manager (30 minutes)

3. On-site interview, 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

Laminar is committed to building a diverse and inclusive team. Even if you are unsure you are 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.

* Please ensure you add the runlaminar.com domain to your safe senders list to ensure you receive our communications.