Company Description

We’re the world’s leading sports technology company, at the intersection between sports, media, and betting. More than 1,700 sports federations, media outlets, betting operators, and consumer platforms across 120 countries rely on our know-how and technology to boost their business.

Job Description

In April 2022, Sportradar acquired VAIX, a company who creates deeply integrated and powerful corporate AI solutions, enabling B2C internet businesses to utilize the power of machine learning for their customers and operations.

Who we are

• VAIX is on a mission to use AI to transform human capability and business opportunity in online gaming. We are a subsidiary of Sportradar, means lots of data to play with.
• First to market, we brought Netflix and Spotify to online gaming, and acquired by Sportradar in 2022, we are looking for innovative people to keep us on the forefront of the industry.
• Our journey began in online gaming, where we leverage the extraordinarily rich data flows and our deep vertical knowledge of that space to transform entertainment and loyalty. Thanks to our union with Sportradar we can use the industry’s biggest source of data to create products and interfaces that are more dynamic and exciting because they are deeply personalized.

What we do

• VAIX creates deeply integrated and powerful corporate AI solutions, enabling B2C operators to utilize the power of machine learning for their customers and operations.
• We are building a wide range of Machine Learning algorithms; domain-specific Recommendation engines, human behavior predictive models and Natural Language Processing model.

Explore the opportunity to join us as a Software and ML Engineer to shape the future of sports technology and make an impact on a global scale. Our diverse team of Engineers (Software, DevOps, Q&A) work together to deliver innovative ML SaaS solutions for the iGaming industry. This is a great opportunity for you if you're eager to work on challenging problems and learn new technologies.

The role entails

• Develop and optimize machine learning pipelines.
• Write and optimize database queries to extract and transform data for machine learning models and dashboards.
• Train and evaluate machine learning models using state-of-the-art techniques.
• Experiment with new technologies and approaches to improve the performance of our machine learning models.
• Collaborate with data scientists, engineers, and account managers to ensure that machine learning solutions meet business needs.

Your profile

• Bachelor degree in Computer Science (or proven strong CS/SE background).
• Excellent programming skills, including knowledge and understanding of Python and/or a functional language (preferably Elixir) and/or a low level programming language (C/C++, Java etc).
• Knowledge of ML algorithms and statistical analysis.
• Strong "get things done the right way" attitude.
• Strong willingness to learn new technologies and work on challenging problems.
• Good command of the English language, in spoken and written forms and good communication skills.
• Working experience in Software development is a plus.
• Familiarity in SQL (Postgres) is desirable.
• Proficiency in Linux systems would be beneficial.

Our offer

• We talk sports every day and take the sporting spirit into our daily work.
• Our company benefits support your health and well-being and is matched by a salary and compensation package based on your experience.
• Working at Sportradar gives you a platform to gain international recognition for your expertise.
• This is a chance to work with industry experts to launch and build a career in one of the fastest-growing businesses in the digital sports environment.
• We are a diverse and collaborative global team with a unique spirit, determined to achieve our goals with integrity and focus.

Additional Information

Sportradar is an Equal Opportunity Employer. We are committed to encourage diversity within our teams. All qualified applicants will receive consideration without regard to among other things, your background, status, or personal preferences