Head of Machine Learning

Responsibilities

• Own the Technical Roadmap: Define and execute the long-term machine learning vision, ensuring our models continue to set the industry standard for real-time sports AI.
• Innovation Leadership: Identify new capabilities in ML/AI and translate complex research into performant models that run efficiently on mobile edge devices.
• End-to-End Execution: Orchestrate the entire ML lifecycle — from data collection and annotation strategies to model training, evaluation, and deployment on iOS.
• Cross-Functional Alignment: Work closely with our world-class iOS engineering, product, and design teams to remove roadblocks, integrate models seamlessly, and ensure the high-velocity delivery of core features.
• Team Leadership & Mentorship: Directly manage, mentor, and elevate a talented, high-performing team of machine learning engineers and data scientists, fostering a culture of collaboration, innovation, and technical excellence.
• Empower & Develop: Conduct regular 1:1s, guide career progression, and ensure the team is aligned with the company's strategic goals while proactively removing blockers so they can execute efficiently.
• Performance & Edge Optimization: Edge Computing Mastery: Act as the ultimate advocate for on-device performance, continuously optimizing neural networks for speed, memory, and battery efficiency using Core ML and the Apple Neural Engine.
• Data-Driven Accuracy: Rigorously analyze model performance data to uncover edge cases in real-world environments (varying lighting, camera angles) and propose architectural experiments to increase tracking accuracy and precision.

Requirements

• 5+ Years in Machine Learning / Computer Vision: You have a proven track record of shipping successful, production-grade computer vision models, ideally for consumer or edge-computing applications.
• Proven People Leader: 2+ years of experience directly managing machine learning or data science teams, with a strong ability to recruit, retain, and develop top-tier technical talent.
• Technical Leadership: You have the experience and confidence required to step into a leadership role, quickly auditing existing architectures and taking full accountability for ML outcomes.
• The "Player-Coach" Mentality: You are strategic enough to present the technical roadmap to the Board but scrappy enough to write PyTorch code, debug a model's latency, or review data pipelines.
• Strong Communicator: Exceptional communication skills — you know how to distill complex AI concepts and architectural trade-offs for non-technical stakeholders and product teams.
• Product Passion: Avid user of SwingVision.

Preferred

• Startup DNA: Experience working in a Series A or similar high-growth environment (team size
• Technical Stack: Deep expertise in Python, PyTorch, C++, Swift, and Apple's Core ML framework.
• Academic Mastery: MS or PhD in Computer Science, Statistics or a related major.
• Domain Expertise: Background in sports analytics, kinematics, or a deep understanding of racket sports mechanics.