Head of Machine Learning

About Us

We’re building the future of sport. Bolt6 is a sports technology company at the forefront of visual innovation - from real-time tracking and data overlays, to immersive broadcast graphics and AR experiences. We work across tennis, golf, motorsport, volleyball, and more; partnering with rights holders and broadcasters to elevate how sport is seen, understood, and enjoyed.

What You’ll Do

We are seeking an experienced and strategic Head of Machine Learning to lead our ML team, define technical direction, and scale impactful machine learning solutions across the organisation. You will oversee multiple ML projects, guide a team of engineers and researchers, and ensure alignment between machine learning capabilities and business objectives.

Leadership, Strategy & Ownership

Define and execute the machine learning strategy aligned with company goals and product roadmap

Build, lead, mentor, and scale a high-performing ML team

Establish best practices across model development, deployment, and lifecycle management

Act as the technical authority for machine learning within the organisation

Identify and prioritise high-impact opportunities for ML innovation and deployment

Manage project timelines, resource allocation, and delivery across multiple ML initiatives

Model Development, Implementation and Deployment

Oversee the design and development of state-of-the-art models in areas such as object detection, key-point estimation, segmentation)

Guide architectural decisions, model selection, and technology stack choices

Ensure robust evaluation methodologies, metrics, and validation strategies are in place

Champion optimisation of models for performance, scalability, and efficiency

Oversee deployment of models into production environments (e.g. ONNX, TensorRT, C++ integration)

Ensure high standards for code quality, reproducibility, and maintainability

Drive innovation through research initiatives and proof-of-concept projects

Maintain a high standard of personal technical contribution, writing and reviewing production-quality code across model development, tooling, and deployment infrastructure

MLOps & Infrastructure

Define and implement scalable MLOps practices across the organisation

Oversee the development of robust ML infrastructure, pipelines, and deployment frameworks

Ensure monitoring, alerting, model versioning, and automated retraining systems are in place

Establish best practices for data pipelines, dataset curation, and annotation workflows

Ensure data quality, governance, and integrity throughout the ML lifecycle

Optimise systems for cost, performance, and reliability in cloud environments (e.g. AWS)

Own the end-to-end data lifecycle, from annotation workflow design and tooling through to dataset versioning, curation, and quality assurance

Design and maintain domain-specific data schemas, keypoint definitions, and labelling taxonomies that encode meaningful sport and task context

Build and maintain internal tooling for dataset construction, merging, filtering, and validation across heterogeneous annotation sources

Develop deep domain expertise across target sports and use cases, ensuring model design and evaluation reflects the real-world requirements of elite sport environments

What You’ll Bring

Experience

A degree in a STEM (Science Technology Engineering and Mathematics) subject

7+ years of professional experience in machine learning, with significant time in leadership or management roles

Proven track record of deploying machine learning models to production environments

Experience leading and mentoring ML teams and managing multiple concurrent projects

Strong experience across the full ML lifecycle, from research to deployment and monitoring

Demonstrated ability to define strategy and drive execution in fast-paced environments

Strong decision-making skills with the ability to balance technical and business trade-offs

Technical Expertise

Deep expertise in Python and modern ML frameworks (e.g. PyTorch, TensorFlow)

Strong understanding of machine learning theory, evaluation techniques, and experimental design

Experience with MLOps practices, including CI/CD, containerisation (Docker), and model lifecycle management

Familiarity with cloud platforms (e.g. AWS) and scalable data/ML infrastructure

Experience with computer vision is highly desirable

Strong understanding of data processing tools (e.g. Pandas, NumPy)

Leadership & Soft Skills

Excellent leadership, communication, and interpersonal skills

Ability to influence and align stakeholders at all levels of the organisation

Strategic thinker with a hands-on, problem-solving mindset

Passion for building teams, mentoring talent, and fostering innovation

What We Offer

Competitive salary and bonus scheme

A leadership role with significant impact on company strategy and direction

Ownership and autonomy to shape the ML function and roadmap

Opportunity to work in sport at an elite level

Support for learning, development, and career progression

A collaborative, high-performance culture with minimal bureaucracy

Health and wellbeing stipend

Location

There is a choice between working remotely ±3 hours timezone from UK, or we also have offices in London and Winchester.

Diversity & Inclusion

We have a commitment to diversity and inclusion across race, gender, age, religion, and identity. We celebrate differences. We encourage different opinions and approaches to be heard, and we use these to build the best products in the world.

We want you to perform your best at every stage of the recruitment process and are committed to ensuring it is accessible to all. If you need any support or require adjustments to be made, please get in touch with us at [email protected].