Machine Learning Engineer
- Prague, Czech Republic
REVOLUTIONIZE SPORTS THROUGH AI
Stats Perform brings unmatched depth and breadth of data, sports research, news and video content, and unrivaled AI-powered solutions to sports media and broadcasters, technology companies, global brands, sportsbooks, teams and leagues, and fantasy providers.
We are looking for a Machine Learning Engineer to build world-class machine learning platform solutions. You will be responsible for empowering data scientists and AI scientists by developing a collection of industry-strength platform services to greatly improve scientist's productivity and facilitate innovation.
HERE'S YOUR ROLE BROKEN DOWN (NOT ALL OF IT, JUST THE MOST IMPORTANT STUFF)
• Build Stats Performs Machine Learning platform and services to support AI and Data Science use cases.
• Manage the ML lifecycle, including data prep, training data generation, feature engineering, optimization, experimentation, reproducibility, deployment and end-to-end workflow management.
• Enable ML and Deep Learning capabilities at vast scale by developing the necessary systems, tools, technologies and integrations as part of the ML Platform offering.
• Help accelerate the velocity from idea to interference in production.
• Contribute to capabilities around data programming, data augmentation (transformation function), active learning (slicing function) for training data, and transfer learning.
• Engineer the de-bias, ethics, security and compliance aspects of ML pipelines, centralized feature store, model megastore, and inference metrics store etc.
• Work with partners and stakeholders to identify data acquisition opportunities, create requirements, transform large volume data into AI ready high-quality relevant datasets.
• Achieve quality ML data using a triad of people, process & technology.
• Identify, assess and implement 3rd party technologies that may complement Stats Perform capabilities, and accelerate advancement of critical features; maintain strong collaborative relationships with 3rd party technology providers.
DO YOU HAVE THESE ESSENTIALS?
• 3+ years of relevant industry experience in Data & analytics platform or machine learning and data science.
• Bachelor's degree in Engineering, Computer Science, Mathematics, Computational Statistics, Machine Learning or related STEM fields.
• Verbal/written communication and presentation skills, including an ability to effectively communicate with both business and technical teams, and both internal and external stakeholders.
• Experience in projects involving large scale multi-dimensional datastore, complex business infrastructure, and cross-functional teams, and track-record of successfully launched ML projects in production.
• Hands on experience with building enterprise grade machine learning and data platforms
• Familiarity with common machine learning algorithms (random forest, XGBoost, etc.)
• Familiarity with advanced ML techniques (neural networks/deep learning, reinforcement learning, active learning, data augmentation and GAN etc.)
• Experience with high-level programming languages and big data tools and ecosystems.
• In-depth working knowledge of cloud infrastructure such as AWS or Google Cloud.
• Experience in integrating with internal and external complex systems that can scale and demonstrate security, reliability, scalability, and cost efficiency.
HERE'S A LITTLE MORE ABOUT US
Stats Perform collects the richest sports data in the world and transforms it through revolutionary artificial intelligence (AI) to unlock the most in-depth insights for media and technology, betting and team performance. With company roots dating back almost 40 years, Stats Perform embraces and solves the dynamic nature of sport - be that for digital and broadcast media with differentiated storytelling, tech companies with reliable and fast data to power their own innovations, sportsbooks with in-play betting and integrity services, or teams with first-of-its-kind AI analysis software. As the leading sports data and AI company, Stats Perform works with most of the top global sports broadcast companies, tech companies, sportsbooks, teams and leagues.
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