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Technical Delivery Lead - Machine Learning

wearebeyondsportsLondonBeyond Sports
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Salary
Not listed
Job type
Full-time
Work mode
Remote
Experience
Lead
Posted
8 Oct 2026
Status
Open · checked 7d ago

About this role

Based in London, the Technical Delivery Lead role at Beyond Sports focuses on driving machine learning innovation and engineering execution for immersive sports entertainment systems. This hybrid technical and leadership position suits professionals who enjoy balancing hands-on development with guiding engineering squads.

Role Overview

Beyond Sports seeks a Technical Delivery Lead to oversee engineering execution, technical strategy, and machine learning initiatives in London. The position requires spending approximately sixty percent of working time on active engineering tasks like building proofs of concept and solving complex problems. The professional in this role collaborates with machine learning engineers, architects, product teams, and creatives to translate live sports data into interactive digital experiences.

Key Responsibilities

Guide engineering squads in delivering complex artificial intelligence systems while contributing directly to architecture and technical challenge resolution.
Build scalable machine learning pipelines for trajectory prediction and motion synthesis.
Prototype cloud-hosted inference services and participate directly in codebase development to support delivery.
Support teams in applying advanced machine learning techniques like Graph Neural Networks, Transformers, Diffusion models, and real-time geometry pipelines.
Shape engineering standards, delivery practices, and technical governance across the organization.

Requirements

Strong background in software engineering, technical delivery, or technical leadership.
Experience deploying machine learning systems to production environments, covering serving, monitoring, and retraining.
Track record of leading or mentoring engineering squads.
Practical experience building and training deep learning models utilizing PyTorch.
Familiarity with CI/CD workflows and MLOps tools such as MLflow.
Experience working with major cloud platforms including AWS, Azure, or GCP.
Experience with generative models or sequence models applied to any domain.
Strong stakeholder communication skills and delivery planning capabilities.

Nice to Have

Strong comprehension of scalable systems, APIs, and cloud-native architectures.
Understanding of 3D graphics pipelines or real-time data systems.
Experience utilizing game engines or Unity.
Personal interest in team sports or football.

Skills and Tools

PyTorch
MLflow
AWS, Azure, GCP
Transformers, RNNs, Diffusion models, GANs, Graph Neural Networks
Unity

About the Company

Beyond Sports reinvents fan experiences by combining real-time sports data, 3D graphics, and artificial intelligence storytelling. The company partners with major organizations like the NFL, NHL, FIFA, and Disney to visualize sports entertainment. The workplace environment emphasizes fast-paced experimentation, technical ambition, and close collaboration between engineers, artists, and product teams.

How to Apply

To submit an application for this position, visit the official company careers page.

Skills and tech stack

PyTorchMLflowAWSAzureGCPTransformersRNNsDiffusionGANsGraph Neural NetworksUnityMLOpsDeep LearningMachine Learning

Questions candidates ask

What percentage of time is spent on hands-on engineering?

Approximately 60% of the time involves active engineering work, such as building proofs of concept, solving technical problems, improving tooling, and supporting delivery initiatives.

What deep learning framework is required?

Hands-on experience building and training deep learning models in PyTorch is required.

Where is the job located?

The position is located in London.

What specific machine learning domains or models are mentioned?

The role involves sequence models like transformers and RNNs, generative models like diffusion and GANs, as well as Graph Neural Networks and spatiotemporal, time-series, or motion data.

What MLOps and cloud tools are relevant?

Familiarity with MLflow, CI/CD workflows, and cloud platforms like AWS, Azure, or GCP is expected.

Ready to apply?

The application is on the official wearebeyondsports careers page.

Apply on company site