Beyond Sports
Technology
SoftwareArchitect-MachineLearning
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Software Architect - Machine Learning at Beyond Sports. Skills: Machine Learning, Technical architecture, ML systems, Cloud infrastructure. Shape architecture. Shape technical direction”
Industry & Context.
Complex technical challenges; Complex architecture challenges; Complex integration challenges
What They're Looking For.
Must Have
Experience in machine learning engineering, Software architecture experience, Technical leadership experience, Deep expertise in ML systems, Deep expertise in data pipelines, Deep expertise in backend engineering, Deep expertise in cloud infrastructure, Hands-on experience with PyTorch, Hands-on experience with TensorFlow, Understanding of scalable APIs, Understanding of cloud-native systems, Understanding of modern engineering practices, Experience creating Proof of Concepts, Experience evaluating technical approaches, Ability to communicate technical solutions, Experience collaborating across teams, Willingness to work on-site
Nice to Have
Experience deploying ML models, Familiarity with MLOps tooling, Experience with AWS, Experience with Azure, Experience with GCP, Understanding of real-time systems, Understanding of motion synthesis, Understanding of 3D graphics pipelines, Experience with Unity, Interest in football, Interest in team sports
What You'll Do.
Shape technical direction
Shape implementation strategy
Design intelligent systems
Transform live sports data
Create immersive digital experiences
Evaluate approaches for inference pipelines
Evaluate approaches for motion synthesis
Build Proof of Concepts
Review model deployment strategies
Solve architecture challenges
Solve integration challenges
Guide technical implementation
Ensure solutions are scalable
Ensure solutions are reusable
Ensure solutions are maintainable
Align solutions with standards
How You'll Work.
Team & Collaboration
Machine Learning Engineers; Tech Leads; Product teams; Team Architects; Multidisciplinary engineering teams
Communication Scope
Technical solutions; Technical audiences; Non-technical audiences
Full Job Description
JOIN OUR TEAM AS A TEAM ARCHITECT (MACHINE LEARNING FOCUS) AT BEYOND SPORTS 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 th
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