ML Infrastructure Engineer - Edge 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 Insurance

401k with matching

Equity

Flexible PTO

Transportation benefit

Job summary

Laminar is seeking a ML Infrastructure Engineer in Boston to own tooling for training, evaluating, and deploying ML models at scale across edge devices and manufacturing domains. You will enable researchers to run models on large datasets and integrate with existing production infrastructure.

You will collaborate with ML researchers and software engineers, building scalable pipelines, registries, and monitoring to ensure reliable model performance in real-time factory environments.

Qualifications

• Experience training ML models on large-scale data.
• Hands-on with ML platforms and experiment tracking tools.
• Strong Python development and SDK experience.
• Familiarity with SQL, Spark and parquet formats.

Responsibilities

• Develop orchestration tooling to launch modeling jobs on large-scale data.
• Design model testing environments with semi-supervised metrics.
• Build model registries and deployment pipelines for edge devices.
• Develop monitoring tools to detect drift and trigger retraining.
• Collaborate with ML researchers and software engineers to integrate systems.
• Build for our unique use-cases and problems.

Tools

AWS

Databricks

MLflow

wandb

Python

boto3

databricks-sdk

mlflow

jax

pytorch

SQL

Apache Spark

Parquet

Job description

Laminar is seeking a ML Infrastructure Engineer in Boston to own tooling for training, evaluating, and deploying ML models at scale across edge devices and manufacturing domains. You will enable researchers to run models on large datasets and integrate with existing production infrastructure.

You will collaborate with ML researchers and software engineers, building scalable pipelines, registries, and monitoring to ensure reliable model performance in real-time factory environments.