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Senior Machine Learning Engineer
vor 1 Monat
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 DescriptionJoin our division, “Sportradar ad:s”, where we provide data-driven marketing and sponsorship services to the iGaming industry. Our purpose-built tools and services cater to the individual marketing needs of sportsbooks and media publishers worldwide. Imagine working in an environment surrounded by sports data, live play-by-play statistics, virtual sports, microservices, and betting – all while maintaining an agile mindset and a commitment to delivering exceptional value for our customers. We’re passionate about our work and deeply care about our people. If you’re ready for the challenge, join us in growing, innovating, and developing The AI team plays a crucial role in expanding and enhancing our product offerings with cutting-edge Machine Learning (ML) and Generative AI solutions. We leverage AI to unlock new opportunities for our clients, providing smarter, data-driven marketing strategies and automating complex decision-making processes. Additionally, we streamline internal operations by generating in-depth analytics, enabling our teams to work more efficiently and make better-informed decisions.
THE CHALLENGE:
As a (Senior) ML Engineer in the AI team at Sportradar, you will have the opportunity to shape and contribute to all components of our AI stack—from the initial idea to the final product. Your work will span model training and fine-tuning, MLOps, deployment and monitoring, ensuring our AI-driven solutions are scalable, efficient, and impactful.
We follow an experiment-based approach, continuously testing new ideas, analyzing results, and sharing insights across the division to drive innovation. You will collaborate closely with sales and product managers to develop cutting-edge AI solutions that enhance our marketing and sponsorship services. Our technology stack relies on scalable microservices hosted in the cloud, allowing us to build flexible and high-performance AI-powered products.
From a technical perspective, our AI solutions are built on a scalable, cloud-native architecture within AWS. We leverage Infrastructure-as-Code (IaC) with Terraform to ensure consistency and efficiency across our environments. Our backend is predominantly developed in Python, with AWS Lambda powering our serverless compute, Amazon S3 for data storage, and CloudWatch for monitoring and observability. For AI/ML workloads, we rely on Amazon SageMaker and Bedrock, enabling seamless model training, fine-tuning, and deployment. Our analytics stack includes AWS Athena and QuickSight, providing powerful insights to drive data-driven decision-making. Continuous integration and deployment (CI/CD) are managed through GitLab CI, ensuring smooth and reliable software delivery. As an engineering team, we focus on building extensible, well-abstracted, and maintainable systems. Thoughtful refactoring and robust testing practices guide our development process, ensuring high-quality, scalable AI solutions.
Key Responsibilities:
- Contribute and grow as part of a self-organized, agile software development team.
- Build our advertising technologies - from understanding the requirements to creating fully functional data/AI solutions.
- Design and craft highly scalable, fault-tolerant ML/AI systems, while keeping your focus on quality, observability, and security.
- Engage in a supportive, collaborative team environment and contribute to maintaining a positive culture.
- Share ideas and insights with different stakeholders within the division.
ABOUT YOU:
- Professional experience in Data Science, Machine Learning, or AI engineering, with a focus on Natural Language Processing (NLP), Speech Recognition, or Computer Vision. Experience with Generative AI is a strong plus.
- Strong problem-solving skills and the ability to think critically when designing AI-driven solutions.
- Hands-on experience with ML model training, fine-tuning, deployment, and monitoring. Experience with cloud-based solutions (AWS SageMaker and Bedrock) is a strong plus.
- Proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, or Hugging Face.
- Experience working in agile/lean environments, with a mindset for continuous learning and improvement.
- Strong ownership, curiosity, and a drive to explore new AI technologies and methodologies.
YOU MIGHT BE A GOOD FIT IF YOU:
- Enjoy working in an experiment-based environment, with a proactive approach to testing hypotheses, analyzing results, and sharing insights.
- Are comfortable communicating findings, collaborating with cross-functional teams, and contributing to data-driven decision-making.
OUR OFFER:
- A collaborative environment with colleagues from all over the world (Engineering offices in Europe, Asia, and the US).
- Ability to shape your own workday and career via a clearly defined professional and personal development plan.
- Opportunity to work with senior leadership, develop yourself, and build your career within an inspiring and fast-growing company and digital sports environment.
- A vibrant and inclusive community, including Women in Tech and Pride groups which welcome all participants.
- A company culture that promotes social aspects, sports, physical exercise, and fun.
- Innovative and cross-team challenges like ShipIt, office sports tournaments in Darts and Table Tennis, and unique beer brewing competitions.
- Competitive salary and benefits (e.g., retirement pension and insurance plan).
While we value the opportunities to work from home, we truly believe that being together, and sharing ideas, opportunities, trials, and tribulations with teammates make us stronger and more innovative – individually and as a company. We strengthen the fibers of our Company each and every day, just by being together. For this reason, we operate a hybrid model where we are in the office 3 days a week.
The minimum monthly salary for this position is according to the Collective Bargaining Agreement, overpayment will be considered depending on qualifications and working experience.
We relocated to our office near the Nordbahnviertel (Praterstern) in the 2nd district of Vienna in Q1/2024. Due to the top inner-city location, we are excellently connected to the public transport network and the cycle path network and are therefore very easy to reach. In addition, we offer our employees a state-of-the-art infrastructure near the center of the most livable city in the world.
OUR RECRUITMENT PROCESS:
- Initial Screening: A quick chat with our Talent Acquisition Partner to understand your background and expectations.
- Technical: Theoretical Interview: 60 minutes to discuss your technical skills on the theoretical level with the technical team.
- Technical: Coding Interview: 60 minutes of live coding where we do not access the end result but rather the candidate's approach (clean code and thinking process).
- System Design Interview: 60 minutes to solve a high-level problem with certain requirements.
- Final Steps: Receive final feedback while onsite visit might be requested and, if successful, an offer
We keep it simple and aim to wrap up the process within 3 weeks.
At Sportradar, we celebrate our diverse group of hardworking employees. Sportradar is committed to ensuring equal access to its programs, facilities, and employment opportunities. All qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. We encourage you to apply even if you only meet most of the requirements (but not 100% of the listed criteria) – we believe skills evolve over time. If you’re willing to learn and grow with us, we invite you to join our team
Seniority level- Mid-Senior level
- Full-time
Referrals increase your chances of interviewing at Sportradar by 2x
LocationInnere Stadt, Vienna, Austria
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