Edge ML Infrastructure Engineer for Smart Factories

Lever, Inc.; Somerville (MA); On-site; USD 89,000 - 141,000; Full time

Benefits offered by this job

Competitive salary

Equity

401k

Health benefits

Greentown Labs network

Paid time off

Job summary

Laminar is seeking a ML Infrastructure Engineer to own the development of infrastructure and tooling that enables researchers to train, evaluate, and deploy models at scale. You will ensure seamless integration with edge devices and factory-floor deployments across domains.

You will interface with ML researchers and data engineers to build frictionless pipelines, improve model deployment, and scale Laminar’s ML capabilities.

Qualifications

• Proficient with cloud platforms to train and evaluate ML models at scale.
• Experience using experiment tracking and model lifecycle tools (MLflow, wandb).
• Strong Python and SDK skills (boto3, databricks-sdk, mlflow).
• Familiar with SQL, Databricks/Spark, and parquet data formats.
• Engineer who builds easy-to-use tools for researchers.
• Detail-oriented with large-scale ML training and edge deployment challenges.

Responsibilities

• Develop orchestration tooling for researchers to launch modeling jobs (training, fine-tuning, inference).
• Design auto-evaluative test environments using semi-supervised metrics and priors.
• Build model registries and automated deployment pipelines for edge devices.
• Create monitoring tools to detect drift and trigger continuous training pipelines.
• Collaborate with ML researchers and engineers to meet needs and integrate with existing infra.
• Build custom solutions tailored to Laminar's unique use-cases.

Skills

AWS & Databricks

MLflow & wandb

Python & SDKs

SQL & Spark

Research tooling

Edge deployment

Tools

Databricks SDK

boto3

mlflow

Job description

Laminar is seeking a ML Infrastructure Engineer to own the development of infrastructure and tooling that enables researchers to train, evaluate, and deploy models at scale. You will ensure seamless integration with edge devices and factory-floor deployments across domains.

You will interface with ML researchers and data engineers to build frictionless pipelines, improve model deployment, and scale Laminar’s ML capabilities.