(Jr) Machine Learning (ML) Developer

We Love AI Jobs; Somerville, Northern (MA, KY); Hybrid; USD 89,000 - 141,000; Full time

Job summary

Laminar invites an early-career ML Developer to build and refine machine learning models for industrial optimization using proprietary spectral sensors and real-time data. You will collaborate with ML/Data Scientists to bring models from prototype to production, while enhancing preprocessing pipelines and ML tooling in a hybrid work environment.

The role emphasizes experimenting, evaluating model robustness, and improving reliability across domains such as CIP, material identification, and

Qualifications

• Recent graduate or early-career ML developer.
• Experience with sensor data pipelines or production ML workloads is a plus.
• Proficient with Python ML frameworks and data tooling.

Responsibilities

• Build machine learning models for industrial process optimization using Laminar’s sensor data.
• Design experiments and evaluate models for accuracy, generalizability, and robustness.
• Develop sensor-data pipelines, model monitoring, and ML infrastructure with the team.
• Support model reliability with monitoring for drift and anomalies.
• Collaborate with ML/Data Scientists and software engineers to scale training and deployment.

Skills

Python

Tools

PyTorch

JAX

TensorFlow

NumPy

Pandas

Polars

scikit-learn

Job description

# (Jr) Machine Learning (ML) DeveloperLaminar (Formerly H2Ok Innovations)Somerville, MA (Hybrid)Full-time$89,000 – $141,000 / yearAI tools:PyTorchJAXTensorFlowUpload your resume once and Scout applies for youApply with ScoutShare this job:LinkedInXSave imageThis early-career developer will build and refine machine learning models used to optimize industrial fluid and process manufacturing. The work spans sensor-data pipelines, model experiments, reliability monitoring, and production ML tooling, in collaboration with ML and data scientists.* Permanent* Hybrid* Recent graduate### Skills and expertisePythonPyTorchJAXTensorFlowNumPyPolarsPandasscikit-learn### Key responsibilities* Build machine learning models for industrial process optimization using Laminar’s sensor data.* Design experiments and evaluate models for accuracy, generalizability, and robustness.* Develop sensor-data pipelines, model monitoring, and ML infrastructure with the team.## How this job comparesCompared with 37 open junior machine learning jobs on October 10, 2026.Pay: This job pays $89K to $141K a year. The 12 open junior machine learning jobs that publish US pay start at $128K on average, so this job starts about 31% lower.Similar open jobs: We Love AI Jobs lists 37 open junior machine learning jobs at 26 companies.Remote work: This job is hybrid. 0 of the 37 junior machine learning jobs (0%) are remote.AI in this role: High. AI is the core of the work: building, training or deploying AI systems. Developing and evaluating machine learning models is the core of the role. The models use spectral and multimodal sensor data to support real-time understanding and optimization of manufacturing processes.## Full descriptionMachines 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.The RoleAs our company grows and scales, we are excited for a ML Developer to join the team! We are looking for ambitious, hard-working recent graduates who want to be at the forefront of bringing AI to fluid & process manufacturing. As a ML Developer, you will own the development and refinement of Laminar’s machine learning models – the heart of our process optimization technology. Your work will affect all of Laminar’s key process optimization models across domains including (but not limited to): CIP (clean-in-place), product changeovers, material identification, and emerging use-cases.You’ll work closely with ML/Data Scientists to bring cutting-edge models all the way from prototype to production. This entails scaling up model training methodologies, crafting experiments, and running ablation studies across a wide and diverse range of domains, all with the goals of increasing model accuracy and reliability. Your work will be instrumental to hyper-scaling Laminar’s solutions and unlocking key markets through enabling new use-cases.What You Will Do• Build machine learning models that usher in the next generation of data-driven, fluid-based industrial processes powered by Laminar's proprietary spectral sensors and software platform• Design and run experiments to evaluate and select machine learning models that are generalizable, accurate, and robust to day-to-day process variability• Work with spectral and multi-modal sensor data, building preprocessing and feature extraction pipelines that can derive insights from noisy, real-world sensors• Support model reliability by developing monitoring (and correction systems, when applicable) for model drift, sensor drift, and process anomalies• Develop performant ML infrastructure and tooling in collaboration with ML/Data Scientists and software team members• Work across problem domains including chemometrics, hybrid modeling, and self-supervised learning. Modeling tasks include distribution modeling, drift and anomaly detections, similarity analyses, and continuous calibrationAbout You• Proficient in at least one Python ML framework (PyTorch, JAX, TensorFlow)• Fluent with Python packages for numeric computing and data workflows (e.g. NumPy, Polars, Pandas, scikit-learn)• An engineer who favors clean, testable code and has a proven track record of delivering high-quality work on a timeline• An executor who thrives with direction and can independently complete technical project objectives• Someone detail-oriented who has a natural curiosity about data. You are enthusiastic to test out hypotheses, understand in detail how our models work, and run physical experiments to improve our modeling capabilities.