Software Architect - Machine Learning

Are you excited about machine learning, technical architecture, and building the intelligent systems powering the future of sports entertainment?

At Beyond Sports, we don’t just visualize sports - we reinvent how fans experience them. Together with partners like NFL, NHL, FIFA, and Disney, we push the boundaries of real-time sports data, 3D graphics, and AI-driven storytelling.

If you’re passionate about machine learning architecture, scalable technical solutions, and guiding engineering teams through complex technical challenges, this could be your next move.

What Your Day Will Look Like

As a Team Architect (Machine Learning Focus), you’ll act as the specialist technical authority within your discipline - helping shape the architecture, technical direction, and implementation strategy behind our ML-driven products and platforms.

You’ll work closely with Machine Learning Engineers, Tech Leads, Product teams, and other Team Architects to design intelligent systems that transform live sports data into immersive digital experiences.

Your role combines strategic thinking with hands-on technical leadership. One day you might be evaluating approaches for scalable inference pipelines or motion synthesis systems. The next, you could be building Proof of Concepts, reviewing model deployment strategies, or helping squads solve complex architecture and integration challenges.

You’ll guide technical implementation across areas such as trajectory prediction, motion synthesis, real-time data processing, 2D-to-3D geometry pipelines, and cloud-hosted ML services.

You’ll also ensure solutions are scalable, reusable, maintainable, and aligned with wider engineering standards across the business.

What We Value

At Beyond Sports, we move fast, experiment boldly, and trust our people. We believe the best results happen when engineers, ML specialists, artists, and creatives work closely together to build things that genuinely haven’t existed before., * High impact: Your work helps shape how millions experience sports globally

• Technical ownership: Influence implementation strategy, architecture, and engineering standards
• Hands-on innovation: Build POCs and help define the future of our ML systems
• Constant learning: From machine learning research to real-time 3D systems, there’s always something new
• Real collaboration: Engineers, artists, ML specialists, and product teams working side by side

And we make sure it’s a great place to work:

• 25 days of paid leave per year
• Pension program
• Lunch included
• Gym card
• Fresh fruit, great coffee, and Friday drinks
• Bi-monthly team outings
• Office games like FIFA, chess, and ping-pong
• Sony Benefits and much more!

Do you have experience in Unity?, You enjoy designing scalable systems and turning complex technical ideas into practical solutions.

Think in systems and implementation strategy

You naturally balance innovation, scalability, maintainability, and delivery requirements.

Stay hands-on technically You enjoy prototyping, validating ideas through code, and supporting engineers with difficult technical challenges.

Collaborate naturally

You can communicate technical approaches clearly across disciplines and with non-technical stakeholders.

Care about quality and reusability

You value maintainable systems, reusable tooling, and strong engineering standards., * Strong experience in machine learning engineering, software architecture, or technical leadership

• Deep expertise in a relevant technical domain such as ML systems, data pipelines, backend engineering, or cloud infrastructure
• Hands-on experience with PyTorch, TensorFlow, or similar ML frameworks
• Strong understanding of scalable APIs, cloud-native systems, and modern engineering practices
• Experience creating Proof of Concepts and evaluating technical approaches
• Ability to communicate technical solutions clearly to technical and non-technical audiences
• Experience collaborating across multidisciplinary engineering teams
• Willingness to work on-site in our Alkmaar office

Nice to Have (But Not Required)

• Experience deploying ML models into production environments
• Familiarity with MLOps tooling such as MLflow, CI/CD workflows, and model monitoring
• Experience with AWS, Azure, or GCP
• Understanding of real-time systems, motion synthesis, or 3D graphics pipelines
• Experience with Unity or other game engines
• Interest in football or team sports