O pozici
Stats Perform is the market leader in sports tech. We provide the most trusted sports data to some of the world's biggest organizations, across sports, media, and broadcasting.
Through the latest AI technologies and machine learning, we combine decades' worth of data with the latest in-game happenings. We then offer coaches, teams, professional bodies, and media channels around the world, access to the very best data, content, and insights. In turn, improving how sports fans interact with their favourite sports teams and competitions.
Co budeš dělat
- Developing and deploying tools and services for training and inference of machine learning models using Python, AWS, Kubernetes, and Terraform.
- Working closely with AI/DS teams to productionize new ML models, ensuring seamless transition from research to production.
- Driving improvements in ML lifecycle management using MLOps and LLMOps best practices.
- Ensuring seamless real-time model serving for high-performance AI applications across multiple sports.
- Monitoring infrastructure costs, resource usage, and system health — proactively identifying inefficiencies, reacting to anomalies, and planning optimisation actions to ensure sustainable and cost-effective platform operations.
- Exploring and applying the latest tools for working with LLMs and Generative AI models.
- Providing technical guidance to various teams on MLOps approaches, deployment strategies, and platform capabilities.
- Supporting, training, and mentoring team members on ML infrastructure and deployment best practices.
Koho hledáme
- 4+ years of commercial experience in software engineering, including at least 2 years in ML Engineering roles such as MLOps Engineer, ML Platform Engineer, or similar infrastructure-focused positions.
- Expert proficiency in Python and strong experience with cloud deployment on AWS.
- Hands-on experience with Kubernetes for orchestrating ML workloads at scale.
- Experience scaling cloud and on-premise architectures, including real-time ingestion, training, deployment, and monitoring of ML models.
- Familiarity with MLOps frameworks (MLflow, Ray, Kubeflow) and modern data pipeline orchestration (Airflow).
- Familiarity with ML frameworks such as PyTorch, Scikit-learn, and others.
- Understanding of CI/CD pipelines (Jenkins, GitHub Actions) and infrastructure-as-code (Terraform).
- Strong problem-solving skills and ability to collaborate effectively with cross-functional teams.
- Fluency in English; good verbal and written communication skills, including an ability to effectively communicate with both technical and non-technical stakeholders.
Benefity
- We love sports, but we love diverse thinking more!
We know that diversity brings creativity, so we invite people from all backgrounds to join us. At Stats Perform you can make a difference, by using your skills and experience every day, you'll feel valued and respected for your contribution.
- We take care of our colleagues
We like happy and healthy colleagues. You will benefit from things like Mental Health Days Off, ‘No Meeting Fridays,’ and flexible working schedules.
- We pull together to build a better workplace and world for all.
We encourage employees to take part in charitable activities, utilize their 2 days of Volunteering Time Off, support our environmental efforts, and be actively involved in Employee Resource Groups.
- Diversity, Equity, and Inclusion at Stats Perform
By joining Stats Perform, you'll be part of a team that celebrates diversity. A team that is dedicated to creating an inclusive atmosphere where everyone feels valued and welcome. All employees are collectively responsible for developing and maintaining an inclusive environment. That is why our Diversity, Equity, and Inclusion goals underpin our core values.
With increased diversity comes increased innovation and creativity. Ensuring we're best placed to serve our clients and communities. Stats Perform is committed to seeking diversity, equity, and inclusion in all we do.
