TetraScience

Senior Product Manager – Model Hosting Infrastructure

TetraScience

full-time

Posted on:

Location Type: Remote

Location: United States

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Job Level

Senior

Tech Stack

AWSAzureCloudGRPCKubernetes

About the role

  • Dual Service Strategy (Inference & Training): Define the roadmap for two core service pillars:
  • Training Services: Orchestrating elastic, cost-optimized compute (GPU/CPU) for model training and experiment tracking.
  • Inference Services: Managing the deployment of models into high-availability, low-latency API endpoints.
  • Ease of Development & Deployment: Radicalize the user experience for ML Engineers. You will build self-service "push-button" deployment workflows that abstract away the complexity of Kubernetes and cloud networking.
  • Lineage & Reproducibility: Ensure every model has a clear "paper trail." You will define how we capture the lineage between data versions, training code, and production artifacts—a critical requirement for Biopharma compliance.
  • Observability & Governance: Build the tools to monitor model health in production. This includes infrastructure-level metrics (latency/memory) and model-level observability (drift/performance) to ensure system reliability.
  • Technical Stakeholder Engagement: Partner with Scientific IT and Platform Engineering to ensure our services integrate seamlessly with existing enterprise identity (IAM) and security frameworks.
  • Backlog & Execution: Act as the "CEO of the Service," translating complex infrastructure needs into clear, actionable epics and user stories for a high-performing engineering team.

Requirements

  • 7+ years of Technical Product Management experience, specifically within cloud infrastructure, backend services, or developer platforms.
  • Deep understanding of the ML Lifecycle: You should be intimately familiar with the infrastructure requirements for both model training (e.g., job scheduling, distributed compute) and inference (e.g., autoscaling, REST/gRPC APIs).
  • Infrastructure Fluency: Strong background in container orchestration (Kubernetes), cloud providers (AWS/Azure), and CI/CD pipelines.
  • Platform Mindset: A track record of building "internal products" or APIs where the primary customer is a developer or a data scientist.
  • Education: Bachelors or Masters degree in Computer Science, Engineering, or a related technical field.
Benefits
  • 100% employer-paid benefits for all eligible employees and immediate family members
  • Unlimited paid time off (PTO)
  • 401K
  • Flexible working arrangements - Remote work
  • Company paid Life Insurance, LTD/STD
  • A culture of continuous improvement where you can grow your career and get coaching
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
Technical Product ManagementML LifecycleModel TrainingModel InferenceContainer OrchestrationKubernetesCloud InfrastructureCI/CD PipelinesREST APIsgRPC APIs
Soft Skills
Stakeholder EngagementCommunicationLeadershipOrganizational SkillsProblem SolvingUser Experience DesignExecutionCollaborationActionable PlanningAdaptability