opengreenhouseivp
Director, AI & Machine Learning
Hello Heart
LocationTel Aviv, Israel
Last observed2026-06-13 05:23:35.348813
Job idivp-hello-heart:greenhouse:8546796002
About Hello Heart: Hello Heart is on a mission to make heart attacks a thing of the past. We’re an AI company focused exclusively on heart health, building a platform that predicts and prevents cardiac events before they happen—identifying risk up to 10 days in advance versus 10 years in traditional clinical models. This is already working at scale. Hello Heart has been shown to reduce inpatient hospital days by 47% and deliver ~$1,800 in annual savings per member. Hello Heart is the cardiac prevention partner to over 80% of large U.S. health plans and serves hundreds of public and private employers. We’re defining how the #1 cause of death—heart disease—is managed in the AI era. Join us. About the role: As the Director of AI & ML you will serve as the strategic and technical anchor for our Israel based AI and Machine Learning functions reporting directly to the VP of Data & AI. You will own the delivery of the core capabilities that power our product bridging the gap between high level business strategy and production grade AI execution. This is a high impact leadership role designed for a senior technical partner who can drive cross organizational alignment across Product, Engineering and Platform teams. We are looking for a leader who moves beyond a traditional management layer to represent the DS/AI function in leadership discussions and strategic planning while maintaining a close operating rhythm with global leadership. In this role you will ensure our AI initiatives are integrated into the heart of the product lifecycle while serving as a credible senior partner for the technical leads. You will be responsible for shaping the future of how our organization builds and scales intelligent systems that handle sensitive healthcare data with precision and scalability. Scope & Team This role owns two teams within the Data & AI group: AI Team: Builds patient-facing AI capabilities, NLP models, and clinical decision-support features. ML Team: Owns production ML pipelines, model monitoring, and machine learning infrastructure. Beyond direct team management, this role carries significant cross-organizational strategic responsibility: Product interface: Bridge the gap between PMs and DS/AI team leads. The TLs are invested at the project level — this Director operates at the strategic level, ensuring AI/ML priorities are shaped early in the product lifecycle, not bolted on after. Be a force of change in how Product and DS/AI collaborate. Engineering interface: Work peer-to-peer with engineering directors on shared execution dependencies, technical architecture decisions, and resource planning. Own this relationship at the Director level rather than leaving it to individual TLs. Platform interface: Partner with Platform on infrastructure, data pipelines, and tooling strategy that underpins ML/AI delivery. Ensure DS/AI needs are represented in platform roadmap decisions. Responsibilities: Day-to-day leadership: Set direction, unblock teams, drive execution cadence for the AI and ML teams Technical strategy & roadmap: Translate function-level strategic priorities into a concrete DS/AI roadmap for Israel. Own and maintain the roadmap. Planning cycles: Run quarterly and yearly planning — present to VP for review and approval Priority decisions: Make mid-quarter tradeoff calls. Escalate to VP only for strategic shifts or budget changes. People leadership: Hiring, performance management, career development, team culture for DS/AI teams Technical architecture: Serve as the senior technical voice on AI/ML design decisions and direction Strategic cross-org interface: Serve as the DS/AI strategic counterpart to Product leads, Engineering directors, and Platform directors. Elevate conversations from project-level coordination (which TLs handle) to strategic alignment on roadmaps, priorities, and architecture. Product-AI integration: Bridge the gap between PMs and DS/AI teams. Drive a shift toward AI-informed product thinking — shaping bets earl
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