Machine Learning (ML) Delivery Engineer

Somerville, MA

Solutions and Applications Engineering

{}

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 scales, we're in search of a full-time ML Delivery Engineer to join our expanding team. As an ML Delivery Engineer, you will work directly with customers to solve high-impact immediate problems, designing and deploying ML models and solutions to build the future of the autonomous factory. Your responsibilities will look similar to those of a hands-on AI startup CTO where you will work cross-functionally in sales, customer success, and engineering to own delivery of high-stakes projects with global clients. You are someone who is highly motivated and enthusiastic about working with data, experienced with (or deeply interested in) machine learning, keen at understanding customer needs, and has excellent communication and problem-solving skills. Having a background in computer science, chemical engineering, industrial engineering, mechanical engineering, UI/UX, or manufacturing processes is a plus.

What You Will Do

Analyze data from some of the largest factories in the world to identify process inefficiencies and areas of potential optimization. For example, analyzing real-time product quality, filtration efficacy, efficacy of cleaning processes, wastewater strength, viscosity, moisture content, particle size, product loss, COD, BOD, etc.
Train, evaluate, and deploy machine learning models to unlock additional factory uptime and deliver time, energy, and water savings.
Present model results to internal and external stakeholders. Demo H2Ok’s data analytics platform live with customers to give them a thorough understanding of their data. Ensure customers thoroughly understand and agree with ML model results, data insights, and savings calculations.
Collaborate with front-end developers to display complex data, trends, and abnormal behavior in an intuitive way. Identify areas of customer confusion and suggest platform improvements to prevent these pain points in user experience. Communicate customer feedback on H2Ok’s data analytics platform to H2Ok engineers.
Identify anomalies and abnormal behavior in real-time based on sensors, controls, and operational data. Communicate these anomalies with customers to ensure they understand the first principles behind why we’ve identified anomalous behavior.
Apply critical thinking and first principles knowledge to solve challenging, real-world problems in factories, breweries, food & beverage facilities, and more.
Collaborate with data scientists, software engineers, and customer stakeholders to ensure models are performant, reliable, and aligned with customer needs.

About You

Fluent in analyzing, understanding, and communicating about data, especially time-series data.
Willing to work directly with customers to explain model results, data analysis, and conclusions from data in a clear, engaging, and succinct way.
Skilled in data storytelling and visualization.
Can create engaging, colorful visualizations for customers that bring data to life and provide insight.
Experienced with presenting data and communicating results to both technical and non-technical audiences.
Experienced with Python, including numerical libraries (such as NumPy and Pandas) and ML frameworks (such as Scikit-Learn, PyTorch, TensorFlow, JAX).Familiar training, fine-tuning, and evaluating performance of machine learning models.
Familiar with SQL or similar database systems (such as MySQL, PostgreSQL, MongoDB).
Experienced with Git or other version control systems.
Familiarity with cloud platforms such as AWS, Azure, or Google Cloud is a plus.
Analytical thinker with the ability to solve complex problems efficiently.
Excellent communication skills to articulate technical issues, solutions, and progress effectively.
Adaptability to learn new technologies and adapt to evolving project requirements.
Strong team player mindset, comfortable sharing knowledge and collaborating within a team environment.
Familiarity with industrial processes and manufacturing (PLC/SCADA/DCS) is a strong plus. Examples of this data: flow rate, conductivity, temperature, pH, water hardness, COD, BOD, viscosity, etc.

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
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 H2Ok's precision automation to cut time & water usage

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.