Head of Machine Learning

SwingVision; Berkeley (CA); On-site; USD 150,000 - 250,000; Full time

Benefits offered by this job

Equity

Performance-based bonus

PTO

401(k)

Medical, dental & vision

Job summary

SwingVision is seeking a Head of Machine Learning in Berkeley, CA, to lead the machine learning team. The role involves owning the ML lifecycle from research to deployment while enhancing the app's computer vision capabilities. Candidates should have over 5 years of experience in machine learning / computer vision, strong management skills, and proficiency in Python, PyTorch, and Core ML. The annual salary ranges from $150,000 to $250,000, along with perks including equity, bonuses, and comprehensive health benefits.

Qualifications

• 5+ years in Machine Learning / Computer Vision with proven success.
• 2+ years of experience managing ML or data science teams.
• Exceptional communication skills for technical concepts.

Responsibilities

• Define and execute the long‑term ML roadmap.
• Identify new capabilities in ML/AI for mobile edge devices.
• Manage the entire ML lifecycle from data to deployment.

Skills

Machine Learning

Computer Vision

Python

PyTorch

C++

Swift

Core ML

People Management

Cross-Functional Communication

Education

MS or PhD in Computer Science, Statistics or related major

Tools

Core ML

Job description

Head of Machine Learning

We are currently seeking a Head of Machine Learning to lead our machine learning team. You will own the machine learning lifecycle from research to deployment, driving the computer vision capabilities that power our category‑defining app.

The annual salary range for this role is $150,000-$250,000. The final salary will be based on a number of factors, including the candidate's experience, qualifications, and location.

Additional benefits include: equity, performance‑based bonus, PTO, 401(k), and medical, dental & vision.

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 iOS engineering, product, and design teams to remove roadblocks, integrate models seamlessly, and ensure high‑velocity delivery of core features.
• People Management: Directly manage, mentor, and elevate a talented, high‑performing team of machine learning engineers and data scientists.
• Empower & Develop: Conduct regular 1:1s, guide career progression, and remove blockers so the team can execute efficiently.
• Edge Computing Mastery: 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 and propose architectural experiments to increase tracking accuracy and precision.

Qualifications

• 5+ Years in Machine Learning / Computer Vision with 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 and recruiting, retaining, and developing top‑tier technical talent.
• Technical Leadership: Experience evaluating architectures and taking full accountability for ML outcomes.
• The “Player‑Coach” Mentality: Strategic enough to present technical roadmaps to the Board but scrappy enough to write PyTorch code, debug latency, or review data pipelines.
• Strong Communicator: Exceptional communication skills to distill complex AI concepts for non‑technical stakeholders and product teams.
• Product Passion: Avid user of SwingVision.
• Startup DNA: Experience working in a Series A or similar high‑growth environment (team size <50).
• 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 related major.
• Domain Expertise: Background in sports analytics, kinematics, or deep understanding of racket sports mechanics.

EEO Statement

SwingVision is an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.