Machine Learning Engineer
Stats Perform is the market leader for Sports AI. We bring the deepest breadth of data, sports research, news and video content, and unrivaled AI-powered solutions to media and broadcasters, technology companies, global brands, sportsbooks, fantasy providers, teams and leagues. Stats Perform powers storytelling through natural language generation for broadcasters and tech companies, unlocks boundless player props and precise projections for sportsbooks, and generates predictions to improve team performance and player evaluation. With more than 20 AI patents issued or submitted, Stats Perform is the leading innovator in sports. We are committed to revolutionizing sports through AI.
Stats Perform's extensive list of customers includes four of the top-five most popular global sports broadcast companies, seven of the top-10 global tech companies, all of the top-10 sportsbooks and seven of the top-10 football (soccer) franchises. We collect more than 30 million unique data points and distributes them to more than 1,800 customers, reaching over three billion fans a year. Stats Perform employs more than 1,600 full-time employees across 25 countries and is home to the largest sport-focused AI team with more than 40 artificial intelligence scientists collaborating with over 100 engineers creating AI solutions. These innovations will be the foundation of the future strategy of the new entity allowing rights-holders, leagues, media, and gaming partners to derive the most value and develop the richest experiences for over 3 billions sports fans.
As you can imagine, such an ambitious vision takes a great team with a strong desire to explore and innovate. We are growing our AI teams to improve and expand our core technologies and help solve many unique and interesting problems around sensing, tracking, understanding and predictions. And, in building new products that never existed before, we are redefining how fans worldwide experience sports.
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 scientists productivity and facilitate innovation. Your responsibilities include, but not limited to:
● Build Stats Perform's Machine Learning platform and services to support major 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 metastore, 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
● 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
● An open minded, structured thinker
● A team player and consensus builder
● Intellectual curiosity and excellent problem-solving skills, including the ability to structure and prioritize an approach for maximum impact
● 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 are able to scale and demonstrate security, reliability, scalability, and cost efficiency