Machine Learning Engineer - Sports AI

Hawk-Eye Innovations Ltd
Bristol
16 hours ago
Create job alert

Location: One of our Basingstoke, Bristol, or London offices (Hybrid – 2 days in the office per week minimum)


Team: Machine Learning


Salary: £39,500 - £48,000


Start Date: As soon as possible


Join Our Team as a Machine Learning Engineer at Hawk-Eye Innovations:

Hi, I’m Lachlan, Technology Lead for the HawkAI team. I’m excited to invite you to apply for the Machine Learning Engineer position in our R&D team at Hawk-Eye Innovations. If you're passionate about defining the future of sports analytics, this could be the ideal role for you.


As a Machine Learning Engineer, you'll be at the heart of our development lifecycle. You’ll work closely with product managers, data stakeholders, and engineers across Data and Machine Learning Teams.


What Your Week Could Look Like:

A typical week might include:



  • Integrating cutting‑edge ML features into HawkAI analysis products
  • Running ML models on live streams of tracking data
  • Designing algorithms to turn ML outputs into actionable insights
  • Helping to develop and deploy machine learning models with a focus on real‑time performance
  • Building cloud and containerised systems for deployment at scale
  • Developing CI/CD and production pipelines to maintain robust software practices
  • Collaborating with product managers and engineers
  • Working with data teams to collect, store, and curate training data
  • Streamlining ML operations and performance pipelines

If you're passionate about defining the future of sports analytics and excited to work with cutting‑edge deep learning methods, this could be the ideal role for you. And then integrating deep learning models into HawkAI Analysis Products


Tech Stack and Skill Requirements:

Required:



  • Python programming fundamentals
  • PyTorch
  • Linux & Windows 10 development experience
  • GIT, GitHub and collaborative software development

Nice‑to‑Haves:



  • AWS (S3, SageMaker, Lambdas)
  • MLOps, CI/CD processes
  • Docker and containerised deployments
  • PyTorch‑Ignite
  • TypeScript & Semantic UI React
  • SSH and secure deployment workflows

Bonus Skills:



  • JIRA & Confluence
  • ClearML

What We Value:

At Hawk‑Eye, our culture is built on openness, collaboration, and technical excellence. Here’s what we value in our team members:



  • Autonomy & Accountability – We trust our engineers to own their work and deliver impact
  • Mentorship & Leadership – As a senior team member, you’ll lead by example and uplift others
  • Pragmatism – We’re creative and experimental, but always grounded in real‑world application
  • Continuous Learning – From peer code reviews to hack days and conferences, we never stop growing
  • Collaboration – We work cross‑functionally and communicate with transparency and empathy

Equal Opportunity Employer:

Hawk‑Eye is committed to fostering an inclusive and diverse workplace. We ensure all employees are treated fairly, regardless of gender, marital status, race, nationality, religion, age, disability, or union membership status. We value diversity and strive to create an environment where everyone can reach their full potential.


Apply Today!

This is a fantastic opportunity to join Hawk‑Eye Innovations and make a significant impact in the sports technology industry. If you’re excited about solving complex ML problems in real‑time and seeing your work on the world’s biggest sporting stages, we’d love to hear from you!


#J-18808-Ljbffr

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer - London

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.