Junior ML Engineer, Industrial AI for Smart Factories

Greentown; Boston (MA); On-site; USD 89,000 - 141,000; Full time

Benefits offered by this job

Medical, Dental, Vision, Life

401k with employer matching

Equity

Greentown Labs membership

Transportation benefit

Paid time off and holidays

Job summary

Laminar, a Greentown Labs startup in the Boston area, seeks a Machine Learning Developer to advance process-optimization models across CIP, product changes, and sensor-driven workflows. You will collaborate with ML/Data Scientists to scale models from prototype to production on real factory data.

The role emphasizes robust pipelines, model evaluation, and exploration of multi-modal sensor data. Recent graduates are welcome in a fast-paced hardware-enabled AI environment with equity and

Qualifications

• Proficient in at least one Python ML framework (PyTorch, JAX, TensorFlow).
• Fluent with Python packages for numeric computing and data workflows (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.

Responsibilities

• 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 calibration

Skills

PyTorch

JAX

TensorFlow

Python

NumPy

Polars

Pandas

scikit-learn

Tools

AWS

GCP

Databricks

Job description

Laminar, a Greentown Labs startup in the Boston area, seeks a Machine Learning Developer to advance process-optimization models across CIP, product changes, and sensor-driven workflows. You will collaborate with ML/Data Scientists to scale models from prototype to production on real factory data.

The role emphasizes robust pipelines, model evaluation, and exploration of multi-modal sensor data. Recent graduates are welcome in a fast-paced hardware-enabled AI environment with equity and