ML Infrastructure Engineer

Laminar (Formerly H2Ok Innovations)

. Develop computer orchestration tooling for researchers to launch modeling jobs for training, fine-tuning, and inference on large-scale data .

Posted 9/24/2026full-timeSomerville • Massachusetts • United StatesMid-LevelSenior💰 $89,000 - $141,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing orchestration tools for machine learning, with a strong focus on AWS, Databricks, and Python. Capable of building automated deployment pipelines and monitoring tools to enhance model performance and support manufacturing processes.

Highest-signal resume keywords

AWSDatabricksPythonMLflowWeights & Biases

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningModel DeploymentModel EvaluationData ProcessingCustom ML Models

Soft Skills

Attention to DetailIndependent Project CompletionCollaboration

Tools & Technologies

Boto3Databricks-sdkMlflowJAXPyTorch

Industry Keywords

Chemical EngineeringProcess EngineeringManufacturingLarge-Scale DataUser-Centric Design

Tech Stack

Tools & technologies

ApacheAWSPythonPyTorchSparkSQL

About the role

Key responsibilities & impact

Develop computer orchestration tooling for researchers to launch modeling jobs for training, fine-tuning, and inference on large-scale data
Design model testing environments that automatically evaluate model performance using semi-supervised metrics and process-aware priors
Build model registries and automated deployment pipelines for model tracking, versioning, and deployment on edge devices
Develop monitoring tools to detect model drift or anomalies and trigger continuous-training pipelines
Collaborate with ML researchers and developers to design systems meeting their needs
Work with software engineers to integrate systems with existing infrastructure
Build tailored solutions for Laminar's unique use cases
Support Laminar's self-driving factory platform, which uses inline sensors, physics- and chemistry-grounded foundation models, process-control software, and analytics to improve manufacturing productivity and sustainability

Requirements

What you’ll need

Highly experienced using AWS and Databricks to train and evaluate ML models on large-scale data
Experience with MLflow and Weights & Biases (wandb) for experiment tracking and model lifecycle management
Highly experienced with Python and SDKs including boto3, databricks-sdk, and mlflow
Familiarity with JAX and PyTorch
Familiarity accessing data through SQL, Databricks/Apache Spark, and raw Parquet formats
Ability to build easy-to-use tools for ML researchers
Strong attention to detail regarding large-scale ML training and edge-device deployment workflows
Ability to independently complete technical project objectives and provide domain expertise for engineering design decisions
Chemical engineering, process engineering, or manufacturing domain knowledge (highly valued)
Experience with spectral, time-series, or sensor data
Experience building or evaluating custom ML models
Experience building real products and practicing user-centric design

Benefits

Comp & perks

Equity
Competitive salary and bonus opportunities
Medical, dental, and vision coverage
Life insurance
Short- and long-term disability insurance
Flexible paid time off
12 company-paid holidays
Employer-matching 401(k)
$90/month transportation benefit
$65/month health and wellness benefit
FSA
Greentown Labs membership
Conference and learning budget
Professional development opportunities
Access to Greentown Labs' extensive network of cleantech startups
Dynamic and inclusive work environment
Team events, rooftop lunches, ping pong matches, and Lunch & Learns