Top Hybrid Machine Learning Engineer Jobs

Lead and scale IAA's data engineering and data science engineering function: define vision and architecture for Azure-based data/BI/ML platforms, drive Microsoft Fabric/Synapse/Power BI implementations, partner with business stakeholders to deliver analytics, forecasting, and ML solutions, mentor and grow teams, and ensure delivery quality, governance, and operational excellence.

Lead enterprise risk adjustment strategy using advanced analytics and ML to maximize risk score accuracy and reimbursement across Medicare Advantage, Medicaid Managed Care, and ACO REACH. Build predictive models, oversee data pipelines, run chart review programs, partner with clinical and finance teams, maintain audit-ready analytics, and present results to executive and board stakeholders.

Work with the CBO and Sales Solutions team to design, prototype, and implement agent-based AI workflows and ML prototypes for life sciences and enterprise use cases. Build demonstrations on Salt's orchestration platform, reproduce research, support model development, research domain requirements, and create reusable templates and documentation for commercial adoption.

Design and implement robust bimanual manipulation algorithms and learning-based robot policies. Build end-to-end autonomy connecting perception, task understanding, and low-level control. Ship production-grade Python and C++ code, optimize system performance, and scale deployments across an industrial robot fleet.

Build the analytical foundation for Trust & Safety: measure abuse, build datasets and dbt models, develop risk and anomaly-detection models, design offline evaluations and experiments, define thresholds and decision frameworks, detect coordinated abuse, embed predictive risk signals into workflows, monitor model drift, and communicate findings to cross-functional partners.

Own the agent-facing integration layer (MCP server) that exposes multimodal video/image AI capabilities to developers and agents. Build auth (OAuth/OIDC/RBAC), multi-tenant isolation, usage tracking, rate limiting, and reliability for enterprise scale. Design API contracts, handle failure modes, and partner with research to productize video understanding features.

Design and build full-stack features for an LLM-powered coaching platform: architect backend services and APIs, integrate models, craft responsive front-end experiences, ensure enterprise-scale performance and security, drive CI/CD and observability, debug across the stack, and mentor engineers while collaborating with product and design.

The ML Bioengineer will conduct research on next-generation clinical and genome language models, collaborating with experts to develop machine learning methodologies and analyze data while contributing to project milestones and documentation.

Design, implement, and optimize machine learning and deep learning models; preprocess and analyze large datasets; integrate models into production; monitor and maintain model performance; collaborate with engineers and stakeholders; stay current with ML/AI advances.

Lead design, development, and production deployment of machine learning models for personalization, recommendations, churn and lifetime value. Partner with product, engineering, editorial, and revenue teams to drive measurable outcomes, perform advanced analytics on large datasets, mentor junior staff, and champion new data science methodologies.