Software Architect - Machine Learning
wearebeyondsports · London ·
- Work mode
- Hybrid
- Category
- ML ai
wearebeyondsports · London ·
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.
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.
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.
You’ll fit right in if you:
Love applied machine learning and technical architecture
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.
Stay curious
You actively follow developments in machine learning, cloud infrastructure, and modern engineering practices.
You don’t need to tick every box, but we’re generally looking for:
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
Experience deploying ML systems into production, including serving, monitoring, and retraining
Familiarity with MLOps tooling such as MLflow, CI/CD workflows, and model monitoring
Experience with AWS, Azure, or GCP
Experience with sequence models (e.g. transformers, RNNs) or generative models (e.g. diffusion, flow, or GANs) — applied to any domain; experience with spatiotemporal, time-series, or motion/trajectory data is a strong plus.
Hands-on experience building and training deep learning models in PyTorch
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
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
Fast-moving, creative, and technically ambitious — that’s our world.
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 - Alkmaar Only
Fresh fruit, great coffee, and Friday drinks
Bi-monthly team outings
Office games like FIFA, chess, and ping-pong
Sony Benefits and much more!
If you’re excited about shaping machine learning architecture, solving complex technical challenges, and building systems that transform how fans experience sports — we’d love to hear from you.
At Beyond Sports, you won’t just design technical solutions.
You’ll help bring sports to life.