Note: The job is a remote job and is open to candidates in USA. The company is an established B2B SaaS technology provider delivering analytics and workflow solutions for the health and human services sector. The Lead Backend Engineer, ML Systems will partner with Data Scientists to productionize machine learning models by designing backend services, deployment infrastructure, monitoring, and reusable engineering frameworks for scalable integration into an existing SaaS platform.
Responsibilities
- Partner directly with Data Scientists to move predictive and statistical ML models from prototype or POC into production
- Design and build backend services and APIs that expose ML predictions, scoring, inference, and other model-driven capabilities to customer-facing applications
- Own the engineering lifecycle from architecture and implementation through deployment, rollout, monitoring, reliability, and ongoing production support
- Establish reusable frameworks, services, and engineering patterns for integrating ML capabilities across the platform
- Make architectural decisions around model serving, infrastructure, scalability, security, maintainability, and build-versus-buy tradeoffs
- Define monitoring and observability approaches for production ML services, including performance, reliability, and model-related production behavior
- Integrate modern AI capabilities such as LLMs, RAG, and agentic workflows where appropriate
- Work within and evolve an established production platform rather than building an isolated greenfield AI environment
- Provide Lead-to-Principal-level technical direction while remaining actively involved in implementation and delivery
Skills
- • Significant software engineering experience with a strong foundation in backend services, distributed systems, and production application development
- • Lead, Staff, or Principal-level experience making architectural decisions and providing technical direction while remaining hands-on
- • Demonstrated experience partnering with Data Science teams to take traditional predictive or statistical machine learning models into production
- • Personal ownership or significant hands-on involvement in productionizing ML systems, including backend integration, deployment, rollout, monitoring, and production support
- • Experience designing scalable and reusable services rather than deploying models as isolated one-off solutions
- • Strong understanding of production engineering practices including cloud infrastructure, CI/CD, testing, observability, reliability, security, and operational support
- • Experience evaluating technical approaches and articulating architectural tradeoffs
- • Ability to work with ML systems that integrate into an existing backend/service-oriented application environment
- • Work Authorization: U.S. Citizens and Green Card holders only
- • This is a 100% remote position within the United States
- • Experience with Java/Spring or integrating ML capabilities with Java-based backend services
- • Python and API frameworks such as FastAPI
- • Model serving, ML pipelines, MLflow, or similar ML production tooling
- • Experience with LLM APIs, RAG, vector databases, prompt engineering, or agentic workflows
- • Experience with analytics, BI, decision-support, or other data-intensive SaaS applications
- • Experience in healthcare, health technology, or human services
- • AWS, Azure, or GCP experience
Benefits
- 100% Remote
- The role is full-time and does not require regular onsite attendance.
Company Overview