[Remote] Machine Learning Engineer

Note: The job is a remote job and is open to candidates in USA. Interwell Health is a kidney care management company focused on reimagining healthcare. They are seeking a Machine Learning Engineer who will be responsible for developing end-to-end machine learning solutions, collaborating with cross-functional teams, and implementing MLOps frameworks.ResponsibilitiesDevelop and deliver end‑to‑end machine learning solutions, including defining technical requirements, architecting scalable systems, and implementing monitoring, logging, and maintenance workflowsCollaborate closely with engineers, product managers, clinicians, and cross‑functional partners to build new ML products and enhance existing systemsLead the design and implementation of MLOps frameworks, including pipeline development, CI/CD integration, drift detection, retraining workflows, and rollback strategiesMonitor model performance in production, identify issues, propose remediation steps, and ensure strong test coverage and system reliabilityUtilize contemporary software engineering practices to implement scalable, secure, and maintainable AI/ML systemsDevelop and customize API integrations to enable seamless connectivity between cloud‑based systems and ML servicesParticipate in architectural discussions to ensure ML platforms meet compliance, performance, and scalability standardsSkillsBachelor's degree in Computer Science, Data Analytics, Software/Computer Engineering, Computational Statistics, Mathematics, or a related discipline3+ years of end‑to‑end ML development in production (data prep, feature engineering, modeling, calibration, deployment, monitoring, maintenance)3+ years of MLOps experience building production pipelines (CI/CD, model registry, feature store), implementing monitoring & drift detection, and automating retraining3+ years of Python for production ML (testing, packaging, type hints, linting) and SQL for analytical and production workloads; Scala a plus2+ years working with distributed compute and cloud ML environments (e.g., Spark/Databricks on Azure/AWS/GCP) and modern data ecosystems (data lakes, DBMS)Strong debugging and optimization skills across data and ML workflowsTrack record of ownership and problem solving—driving measurable impact and quality under ambiguity and evolving requirementsAbility to communicate technical decisions clearly and contribute to documentation and design discussionsDemonstrated system design & architecture skills for scalable, high‑performance ML services and batch/streaming workflows; familiarity with API design and service integration patternsProven understanding of tradeoffs in latency, cost, performance, and compliance1+ years of Databricks experience + some experience in infrastructure/networking1+ years implementing LLM‑based solutions in production (prompt/response design, evaluation frameworks, guardrails/safety, latency/cost optimization)1+ years designing compliant ML platforms (e.g., HIPAA, SOC 2) and working with PHI/PII governance, access controls, and auditabilityCompany OverviewInterWell Health is a national physician-centric partnership between Fresenius Medical Care North America. It was founded in 2019, and is headquartered in Waltham, Massachusetts, USA, with a workforce of 501-1000 employees. Its website is https://interwellhealth.com/.