Garner Health

1 month ago

Senior Machine Learning Operations Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 23 hours agoStatus: Live

Job Summary

Join Garner Health as a Senior MLOps Engineer in the Platform Engineering team to build and operate production ML systems that impact millions of patients. You’ll develop ML platform components (feature store, model registry, ML CI/CD), optimize cost and latency, implement drift monitoring, and collaborate with ML, data, and product engineers in a fast-paced, mission-driven healthcare environment.

Location: New York

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Sr. Manager level

Key Responsibilities

•Ensure reliability, performance, functionality, and cost-efficiency of production ML systems, contributing to SLOs, observability, and on-call duties
•Build key components of Garner's ML platform (data infrastructure like feature store, model registry, CI/CD for models) and standardized service patterns
•Implement ML-specific CI/CD pipelines with automated data quality checks and statistical model validation prior to deployment
•Drive down cost and latency through improved architecture, hardware choices, and model optimization
•Contribute to workflows, standards, and KPIs for the MLOps function and establish drift monitoring for data/concept drift with plans for future Continuous Training architectures

Pay and Benefits

Salary: USD 256,000 - 285,000 annually

Equity and Bonus:Equity

Perks:Health Insurance401kEquityPaid LeaveDental

Key Requirements

•5+ years of software engineering experience with time spent operating ML or data-intensive systems in production
•Hands-on experience with the modern ML production stack (model serving, feature stores, model registries, CI/CD for ML)
•Strong infrastructure and platform engineering fundamentals (Kubernetes, containerization, cloud AWS, Terraform/IaC, observability, incident response)
•Experience building ML platforms or significant components of one (not strictly SaaS) with ability to judge build vs buy
•Strong collaboration across ML, data, platform engineers, data scientists, and product engineering teams

Experience:5+ yearsHealthcareMlopsMachine learningData-intensive systems

Skills:CommunicationCollaborationProblem-solvingLeadershipTeamwork

Languages:English

Tech Stack:PythonKubernetesAWSSagemakerTerraformS3SnowflakeAirflowDatadog

Company Brief

Garner Health

Provides employer-sponsored healthcare navigation and care coordination services, combining personalized digital coaching, benefits navigation, and care management to help employees access appropriate care and reduce healthcare costs.

Industry: HealthTech

Website

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Garner Health

1 month ago

Senior Machine Learning Operations Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 23 hours agoStatus: Live

Job Summary

Location: New York

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Sr. Manager level

Key Responsibilities

•Ensure reliability, performance, functionality, and cost-efficiency of production ML systems, contributing to SLOs, observability, and on-call duties
•Build key components of Garner's ML platform (data infrastructure like feature store, model registry, CI/CD for models) and standardized service patterns
•Implement ML-specific CI/CD pipelines with automated data quality checks and statistical model validation prior to deployment
•Drive down cost and latency through improved architecture, hardware choices, and model optimization
•Contribute to workflows, standards, and KPIs for the MLOps function and establish drift monitoring for data/concept drift with plans for future Continuous Training architectures

Pay and Benefits

Salary: USD 256,000 - 285,000 annually

Equity and Bonus:Equity

Perks:Health Insurance401kEquityPaid LeaveDental

Key Requirements

•5+ years of software engineering experience with time spent operating ML or data-intensive systems in production
•Hands-on experience with the modern ML production stack (model serving, feature stores, model registries, CI/CD for ML)
•Strong infrastructure and platform engineering fundamentals (Kubernetes, containerization, cloud AWS, Terraform/IaC, observability, incident response)
•Experience building ML platforms or significant components of one (not strictly SaaS) with ability to judge build vs buy
•Strong collaboration across ML, data, platform engineers, data scientists, and product engineering teams

Experience:5+ yearsHealthcareMlopsMachine learningData-intensive systems

Skills:CommunicationCollaborationProblem-solvingLeadershipTeamwork

Languages:English

Tech Stack:PythonKubernetesAWSSagemakerTerraformS3SnowflakeAirflowDatadog

Company Brief

Garner Health

Industry: HealthTech

Website