ABOUT US

Launched in 2021, Bolt6 is an Emmy award-winning start-up dedicated to improving the experience of sport for everyone. Our products help to improve fan engagement, officiating acceptance, and drive commercial performance for sports leagues and federations.

We use cutting-edge technology to do a variety of amazing things with cameras and other data sources (all in real-time on site or in the cloud), including:

• Tracking the 3D position of vehicles in elite motorsport (e.g. NASCAR)
• Ball and skeletal player tracking of athletes in a number of top level sports
• Electronic line calling in tennis and volleyball
• Providing the platform for sports federations to make critical officiating decisions using video and tracking data

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.

EXPERIENCE:

• A degree in a STEM (Science Technology Engineering and Mathematics) subject
• Self starter with initiative and the ability to pick up and develop projects independently
• Ability to work quickly and make effective decisions
• Intellectually curious and has the drive to ask the right questions in order to get to the bottom of complex issues
• Experience with A/B testing and experimental design
• Understanding of model evaluation metrics and validation techniques
• Great interpersonal skills
• The ability to quickly grasp complex issues
• The ability to work well under pressure to tight deadlines whilst remaining organised
• Strong analytical approach to problems

TECHNICAL SKILLS:

• Proficiency in Python
• Proficiency with version control (Git)
• Familiarity with containerisation (Docker)
• Familiarity with data processing tools (Pandas, NumPy)
• Experience using machine learning frameworks like PyTorch or TensorFlow
• Familiarity with cloud platforms and their ML services

BENEFITS:

• MOST IMPORTANT: Your career
• Mentorship from senior machine learning engineers
• Access to cutting-edge tools, technologies, and computing resources
• Clear career progression paths within the machine learning engineering discipline
• Access to large-scale datasets and real-world problem-solving opportunities
• We will encourage and support you through learning and development tailored to your role.
• If you are looking for a company where you will be challenged, valued and respected, with great compensation in a team that doesn’t play politics then this is the role for you
• Competitive salary, depending on experience and skill set
• Bonus scheme
• Flexible hours and choice of working remotely
• Ownership and autonomy of your work
• The opportunity to work in sport at an elite level

Soft Skills

• Collaborate with ops team to understand current limitations of models, and come up with solutions of how to fix them.
• Present findings and recommendations to stakeholders in both technical and non-technical formats
• Participate in code reviews and knowledge sharing sessions
• Contribute to team documentation and best practices
• Stay up-to-date with the latest developments in AI, model architecture and infrastructure

ROLE REQUIREMENTS

We are searching for motivated, driven and proactive individuals, who will own a ML-based project, or research block to design, train and integrate a new machine learning models. The role will involve working closely with ML, software engineering and operations teams to ensure the models are well designed, integrated and utilised in our products.

KEY RESPONSIBILITIES:

Model Development, Implementation and Deployment:

• Develop and implement state-of-the-art models for computer vision problems including object detection, key-point estimation, segmentation; using Python, PyTorch, Ignite, OpenCV, AWS
• Evaluate model performance
• Export models to ONNX and deploy and integrate them into our C++ environment using TensorRT
• Optimise existing models for improved accuracy, efficiency, and scalability
• Research and evaluate new machine learning techniques and frameworks
• Build and maintain machine learning infrastructure and deployment pipelines
• Implement model monitoring and performance tracking systems

Data Management

• Dataset generation, annotation and curation for efficient iterations of models
• Implement data and augmentation pipelines for training
• Perform exploratory data analysis to identify patterns and insights
• Ensure data quality and integrity throughout the machine learning life-cycle

Soft Skills

• Collaborate with ops team to understand current limitations of models, and come up with solutions of how to fix them.
• Present findings and recommendations to stakeholders in both technical and non-technical formats
• Participate in code reviews and knowledge sharing sessions
• Contribute to team documentation and best practices
• Stay up-to-date with the latest developments in AI, model architecture and infrastructure.