Robotics ML Platform Engineer: Data Pipelines & Models

Lab37; Warrendale (Allegheny County); On-site; USD 130,000 - 164,500; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k)

Health Savings Account (HSA)

Paid holidays

Paid sick time

Parental Leave

Life & Disability Insurance

Job summary

Lab37 Robotics is seeking a skilled Data Platform Engineer to own the data and ML platform powering our robotics fleet. You will build ETL pipelines, manage ML training infra on Kubernetes, ensure data quality and observability, and own the data warehouse and dashboarding layers for real-time insights.

You will collaborate with data scientists to productionize pipelines and contribute to Terraform-based infrastructure and CI/CD, with on-call rotations to ensure reliability.

Qualifications

• 2+ years in data engineering, ML infrastructure, or analytics engineering.
• Experience with workflow orchestration tools (Argo Workflows, Airflow, Prefect, or similar).
• Python data stack proficiency — pandas, SQL, dbt, and comfort writing production-quality data pipelines.
• Experience with cloud data services (BigQuery, Athena, S3, or GCP equivalents).
• Experience building or maintaining ML training pipelines (not just using them as a consumer).
• Docker containerization and Kubernetes basics.
• SQL fluency — you'll write complex queries daily and care about query performance.
• Familiarity with documentation tools and writing design documents.

Responsibilities

• Build and maintain ETL pipelines that ingest, validate, transform, and load robot telemetry data into BigQuery for analytics and ML training.
• Manage ML training infrastructure using Argo Workflows on Kubernetes — from data extraction through model training, evaluation, and registration.
• Design and maintain data quality checks and observability dashboards (the 'glass panel' for data pipeline health).
• Own the data warehouse layer — schema design, incremental loading, dbt transforms, and BigQuery/Athena query optimization.
• Build dashboard infrastructure (Superset, Grafana) that kitchen operations and leadership teams rely on for real-time insights.
• Collaborate with data scientists to productionize model training pipelines — from notebook experiments to reproducible, automated workflows.
• Contribute to infrastructure-as-code (Terraform) and CI/CD pipelines for data and ML workloads.
• Participate in on-call rotations for data pipeline reliability.

Skills

Data engineering

ML infrastructure

Analytics engineering

Python data stack

SQL proficiency

Data quality & observability

Documentation writing

On-call reliability

Tools

Argo Workflows

Airflow

Prefect

Kubernetes

dbt

BigQuery

Athena

Docker

Grafana

Superset

Terraform

Job description

Lab37 Robotics is seeking a skilled Data Platform Engineer to own the data and ML platform powering our robotics fleet. You will build ETL pipelines, manage ML training infra on Kubernetes, ensure data quality and observability, and own the data warehouse and dashboarding layers for real-time insights.

You will collaborate with data scientists to productionize pipelines and contribute to Terraform-based infrastructure and CI/CD, with on-call rotations to ensure reliability.