Senior ML Data Ops Engineer (Hybrid)

About the position Homeward is rearchitecting the delivery of health and care in partnership with communities everywhere, starting in rural America. Today, 60 million Americans living in rural communities are facing a crisis of access to care. In the U.S. healthcare system, rural Americans experience significantly poorer clinical outcomes. This trend is rapidly accelerating as rural hospitals close and physician shortages increase, exacerbating health disparities. In fact, Americans living in rural communities suffer a mortality rate 23 percent higher than those in urban communities, in part because of the lack of access to quality care. Our vision is care that enables everyone to achieve their best health. So, we’re creating a new healthcare delivery model that is purpose-built for rural America and directly addresses the issues that have historically limited access and quality. Homeward supports Medicare-eligible beneficiaries by partnering with health plans, providers, and communities to align incentives – taking full financial accountability for clinical outcomes and the total cost of care across rural counties. As a public benefit corporation and Certified B Corp™, Homeward’s mission and business model are aligned to address the healthcare, economic, and demographic challenges that make it challenging for rural Americans to stay healthy. Our Homeward Navigation™ platform uses advanced analytics to connect members to the right care and local resources that address social determinants of health and improve holistic health outcomes. Since many rural communities lack adequate clinical capacity, Homeward also employs care teams that supplement local practices and reach people who cannot otherwise access care. Homeward is co-founded by a leadership team that defined and delivered Livongo’s products, and backed most recently by a $50 million series B co-led by Arch Ventures and Human Capital, with participation from General Catalyst for a total of $70 million in funding. With this leadership team and funding, Homeward is committed to bringing high-quality healthcare to rural communities in need. Join us in transforming healthcare for rural America. This role sits at the intersection of machine learning, infrastructure, and data, owning the end-to-end systems from data infrastructure, data ingestion, analytics, ML models, and production services. You’ll partner closely with data science, platform, backend, and clinical teams to ensure our data and ML systems are scalable, reliable, and compliant.

Responsibilities

• Own the production ML lifecycle — deployment, monitoring, scaling, retraining, and reliability of models in production
• Design and maintain CI/CD pipelines for applications, infrastructure, data, and ML artifacts using AWS and GitHub Actions
• Build and operate cloud data infrastructure using infrastructure-as-code (Terraform, CDK) with a focus on security, scalability, and compliance
• Develop and maintain data ingestion and transformation pipelines across structured and semi-structured sources (APIs, files, healthcare data)
• Partner with data science and analytics to ensure high-quality, well-modeled data in Snowflake using dbt and modern ELT tooling
• Implement observability and monitoring across services, data pipelines, and ML models (drift, performance, failures)
• Support regulated workloads (HIPAA / PHI) with strong data and model governance practices
• Contribute to technical roadmap, documentation, and engineering best practices across ML, infra, and data

Requirements

• 6–8+ years of experience across DevOps, MLOps, and/or Data Engineering
• Deep experience with AWS (SageMaker, ECS/EKS, Lambda, ECR, CloudWatch, Step Functions)
• Strong hands-on experience with:
• Infrastructure as Code (Terraform, AWS CDK)
• CI/CD (GitHub Actions preferred)
• Containers & orchestration (Docker, ECS/Kubernetes)
• Advanced SQL and Python skills for data pipelines, automation, and ML workflows
• Experience with modern data stacks (Snowflake, dbt, Airbyte or similar)
• Comfort working cross-functionally in a fast-moving, startup environment

Nice-to-haves

• Experience in healthcare or other regulated domains
• ML monitoring tooling
• Experience building feature pipelines or supporting automated model retraining
• Exposure to genAI tooling and LLM platforms
• Startup or early-stage scaling experience

Benefits

• Competitive salary, equity grant, generous paid time off
• Comprehensive benefits package including medical, dental & vision insurance with 100% of monthly premium covered for employees
• Company-sponsored 401k plan

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