ML Infra Engineer — Cloud Platform for Robotics

Roboticsconnected; Pittsburgh (Allegheny County); On-site; USD 140,000 - 175,000; Full time

Job summary

Lab37 Robotics in Pittsburgh is seeking a senior engineer to own the cloud platform infrastructure powering our robotics fleet. You will design and maintain cloud-based ML pipelines, data ingestion, and model deployment workflows used by data scientists, kitchen operations teams, and field engineers.

The role requires deep experience with ML infrastructure, model registries, and automation, collaborating closely with embedded and cloud engineers.

Qualifications

• 3+ years of experience in Cloud infrastructure, MLOps, and data engineering at scale.
• Hands-on experience designing systems for automated model checkpointing, model registries, and metadata management (e.g., MLflow, Kubeflow etc).
• Strong experience with ML & Cloud workflow orchestration tools (SageMaker, K8, Argo Workflows, Bedrock) and cloud storage architectures.
• Proven track record building self-service ML platforms, pipeline abstraction layers, or automated developer workflows.
• Experience with working with embedded engineers.

Responsibilities

• Design, build, and maintain scalable ML infrastructure that abstracts away underlying storage, pipeline management, and repetitive environment setup tasks.
• Implement robust systems for automated model checkpointing, persistent metadata management, and experiment tracking across distributed training runs.
• Create self-service ML workflows and tooling that empower ML engineers and data scientists to focus on core logic, model architecture, and validation.
• Build and maintain automated ETL and data ingestion pipelines that stream and transform raw robot telemetry into clean datasets for training and analytics.
• Contribute to infrastructure-as-code (Terraform) and CI/CD automation for model deployment, data processing, and cloud services.
• Partner with cloud and embedded engineers to streamline model deployment to fleets of robots in the field and participate in on-call rotations for platform reliability.
• Monitoring & Cost: Track model drift, system throughput, and optimize cloud compute costs.

Skills

Cloud infrastructure

MLOps

Data engineering

Self-service ML platforms

Embedded engineers collaboration

Tools

MLflow

Kubeflow

SageMaker

Kubernetes

Argo Workflows

Bedrock

Job description

Lab37 Robotics in Pittsburgh is seeking a senior engineer to own the cloud platform infrastructure powering our robotics fleet. You will design and maintain cloud-based ML pipelines, data ingestion, and model deployment workflows used by data scientists, kitchen operations teams, and field engineers.

The role requires deep experience with ML infrastructure, model registries, and automation, collaborating closely with embedded and cloud engineers.