ML Infrastructure Engineer at Laminar
- Location
- Boston, United States
- Compensation
- $89k-$141k + Equity
Laminar is teaching machines to understand matter, bringing physical AI to the world's largest food and beverage manufacturers. As an ML Infrastructure Engineer in Boston, you’ll build the orchestration and deployment pipelines that power foundation models on factory floors across six continents.
This is a rare opportunity to join a 2026 World Economic Forum Technology Pioneer backed by tier-one investors. If you want to solve the hardest version of ML—where code meets physics and legacy industrial hardware—this $89k-$141k + Equity role is for you.
What's the next step?
Laminar are hiring from Jack's network. Talk to Jack for free and get a direct introduction to the team, if a good fit.
Role overview
You will own the development of infrastructure and tooling to help researchers train, evaluate, and deploy models at scale. Your work powers the scalability of AI solutions across hundreds of factories globally. You’ll bridge the gap between ML research and production, building compute orchestration and automated pipelines that survive contact with physics.
About Laminar
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.
What you will do
- Develop computer orchestration tooling for researchers to seamlessly launch large-scale training, fine-tuning, and inference jobs on AWS and Databricks.
- Design automated model testing environments and registries to track, version, and deploy champion models to edge devices without human intervention.
- Build sophisticated monitoring tools to detect model drift in industrial environments and trigger continuous training pipelines for self-improving production.
Who this is a fit for
- Proven experience building researcher-facing ML platform tooling from orchestration to deployment using AWS, Databricks, and Python SDKs like boto3.
- Deep proficiency with model lifecycle management tools such as MLflow or wandb and familiarity with modern frameworks like PyTorch or JAX.
- Strong background handling large-scale data via SQL and Spark, with an interest in sensor, time-series, or spectral data in manufacturing contexts.
Why this role is remarkable
- Work on the hardest version of ML where models must survive contact with real-world physics and integrate with decades-old industrial machinery.
- Join a high-traction startup recognized as a WEF Technology Pioneer and Gold Edison Award winner, serving global giants like Coca-Cola and Unilever.
- Gain exceptional ownership in a polymathic team of AI researchers, hardware engineers, and chemists with few layers between identification and impact.
How Jack & Jill work together
What happens next?
Jack’s an AI agent for job searching and career coaching. He works for you.
Jill is the AI recruiter working for the company. She recruits from Jack’s network.
If your profile’s a match and Laminar wants to meet, Jill will make the intro. In the meantime, Jack will send you excellent alternatives.