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Senior Product Manager - Model Hosting Infrastructure

1 month ago
United States
Full-time
Senior
Technical Product Manager
DevOps and Infrastructure
AWS Azure CI/CD Datadog Docker Grafana gRPC Kubeflow Kubernetes Machine Learning MLflow MLOps Prometheus REST API SageMaker Terraform
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TetraScience

TetraScience

TetraScience is the only vendor neutral, open, cloud native platform purpose built for science, providing next generation lab data automation and scientific data management to accelerate scientific discovery and improve human life.

Biotechnology
51-250
Founded 2019
$99M raised
View All Jobs 4

Description

  • Define and own the roadmap for two core service pillars: Training Services (elastic, cost-optimized compute and experiment tracking) and Inference Services (high-availability, low-latency API endpoints).
  • Design and build self-service, push-button deployment workflows that abstract Kubernetes and cloud networking to radically improve developer experience for ML engineers.
  • Specify and implement elastic training environments and high-performance inference services capable of operating at Petabyte scale.
  • Define and implement lineage and reproducibility mechanisms that capture relationships between data versions, training code, and production artifacts for Biopharma compliance.
  • Build observability and governance tooling to monitor infrastructure metrics (latency/memory) and model-level signals (drift/performance) to ensure system reliability in production.
  • Partner with Scientific IT and Platform Engineering to integrate services with enterprise identity (IAM), security frameworks, and existing infrastructure.
  • Own the service backlog and execution: translate complex infrastructure needs into epics and user stories and act as the “CEO of the Service” for the engineering team.
  • Prioritize cost, scalability, and regulatory requirements when shaping service-level features and operational runbooks.

Requirements

  • 7+ years of Technical Product Management experience in cloud infrastructure, backend services, or developer platforms.
  • Deep understanding of the ML lifecycle, including training infrastructure (job scheduling, distributed compute) and inference requirements (autoscaling, REST/gRPC APIs).
  • Strong infrastructure fluency with container orchestration (Kubernetes), cloud providers (AWS/Azure), and CI/CD pipelines.
  • Proven platform mindset and experience building internal products or APIs for developer or data-scientist customers.
  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
  • Preferred: experience with MLOps frameworks such as Kubeflow, MLflow, or SageMaker at Series B–D scale.
  • Preferred: knowledge of Infrastructure-as-Code (Terraform) and observability stacks (Prometheus, Grafana, Datadog).
  • Preferred: background in Life Sciences or Biopharma and familiarity with GxP or regulated data environments.
  • Preferred: ability to work during Eastern Time Zone hours.
  • Note: the company is not currently providing visa sponsorship for this position.

Benefits

  • 100% employer-paid benefits for all eligible employees and immediate family members.
  • Unlimited paid time off (PTO).
  • 401(k) plan.
  • Flexible working arrangements with remote work options.
  • Company-paid life insurance and short-term/long-term disability (LTD/STD) coverage.
  • A culture of continuous improvement with opportunities for career growth and coaching.

Interested in this position?

Apply directly on the company website

Apply Now

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