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Senior ML engineer building and deploying deep learning models (transformers, foundation models, transfer learning) for oncology real-world data. Responsibilities include research and development of predictive models (digital twins, endpoint prediction, trial optimization), extending models across data sources, supporting client engagements, and partnering with product and engineering to productionize reproducible, maintainable solutions while communicating results to technical and non-technical stakeholders.

Design and build complex, business-critical data pipelines and tooling; expand Deep Learning and LLM extraction for clinical insights; collaborate with clinicians, product, and scientists; shape team roadmaps and grow European engineering; iterate rapidly while maintaining quality, security, and compliance with healthcare data requirements.

Design and build complex, business-critical data pipelines and ML/LLM-powered clinical extraction systems. Collaborate with clinicians, product, and global engineering teams to scale solutions, maintain quality and security, and help grow the European engineering organization while developing UK healthcare domain knowledge.

Design and develop technology solutions in partnership with global teams, addressing challenges in cancer care through innovative software engineering practices.

Lead the development and maintenance of integrations with health partners, manage data sources, and enhance oncology infrastructure, ensuring operational excellence and collaboration across teams.

Maintain operational tools and metrics to support real-world evidence deliveries; transform data into actionable insights using statistical methods and visualizations; build and support dashboards and data tools; run ad-hoc analyses, experiments, and predictive models; collaborate with cross-functional stakeholders and operations teams to prioritize and improve processes.

Design, build, automate, and operate cloud-native network infrastructure to ensure reliability, performance, and observability. Drive test-driven infrastructure changes, support office networking, participate in on-call rotations, incident escalations, code/config reviews, and produce documentation and playbooks for the engineering organization.

Design, develop, and deploy secure software and data pipelines to transform patient data into real-world evidence. Build web apps and scalable automated pipelines, ensure data quality and tests, address security and privacy constraints, and occasionally deploy and operate solutions at hospital partner sites.

Own net-new OncoEMR sales for smaller community oncology practices end-to-end, support larger deals with the Director of Sales, grow top-of-funnel pipeline, maintain Salesforce opportunity data, and manage partner intake for the Flatiron Vendor Network. Collaborate cross-functionally with Solution Design, Implementation, Interfaces, Marketing, Legal, and BizOps to build sales playbooks, coordinate demos, and drive deals to contract execution.

Lead US technical recruiting for Machine Learning and Software Engineering teams. Source and build talent pipelines, manage candidate relationships and offers, collaborate with hiring managers and TA peers, and support non-technical and early-career hiring as needed.