Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Machine Learning Engineering Manager | Computer Vision | Deep Learning | Python | C++ | London, Hybrid

Enigma
united kingdom, united kingdom
5 months ago
Applications closed

Related Jobs

View all jobs

Engineering Manager, Machine Learning Platform

Senior Data Scientist

Data Science Manager

Senior Staff Machine Learning Scientist, Operations

Machine Learning Engineering Manager - Personalization

Computer Vision/Machine Learning Research Manager

Machine Learning Engineering Manager | Computer Vision | Deep Learning | Python | C++ | London, Hybrid


We are seeking anEngineering Managerto join ourApplied Machine Learning team, focused on delivering innovative experiences and insights for coaches, athletes, and fans. This role leads high-impact initiatives using advanced computer vision and deep learning technologies at scale—powering sports experiences from elite organizations to local communities.


Key Responsibilities

  • Deliver Results: Independently manage a multidisciplinary team of 5 to 10 Engineers and Data Scientists. Drive progress toward quarterly and annual goals, while ensuring high-impact outcomes for users and the business.
  • Foster Collaboration: Work cross-functionally with other teams and organizational leaders to deliver projects in iterative increments, manage dependencies, and uphold product quality.
  • Set Technical Standards: Lead by example in architectural decisions, code quality, and system health. Guide the team in building reliable, scalable, and cost-effective solutions that support long-term goals.
  • Build High-Performing Teams: Create and nurture an environment where your team is empowered, motivated, and set up for success. Optimize technical processes and team structures for consistent delivery.
  • Talent Development: Provide mentorship and career guidance to Applied Scientists and Engineers, supporting growth across both technical and leadership paths.


Location and Flexibility

This role is open to candidates who live within commuting distance of aLondon office. There are no current requirements for in-office presence, thanks to a flexible work policy.


Required Qualifications

  • Leadership Experience: Proven success in managing a team of 5–10 technical contributors and supporting their development and productivity.
  • Systems Expertise: Hands-on experience in building, maintaining, and monitoring complex AI/ML systems operating in production at scale.


Technical Proficiency: Strong experience in several of the following domains:

  • Classical and deep learning-based computer vision
  • Multi-view geometry
  • GPU-accelerated computing
  • Edge inference
  • Large language models (LLMs)
  • Real-time systems
  • Signal processing


Excellent Communication: Ability to explain complex technical topics and decisions clearly to both technical and non-technical stakeholders.

Product Focus: Track record of delivering impactful ML/AI-driven features in close collaboration with product and engineering teams.


Preferred Qualifications

Sports Technology Experience: Familiarity with applying AI/ML techniques to the sports domain, especially to generate insights or performance data.


What We Offer

  • Flexible Work-Life Balance: Benefits designed to support both your personal and professional life, including generous vacation policies, company holidays, meeting-free days, and remote work options.
  • Autonomy and Ownership: A culture that encourages individual ownership, open communication, and innovation.
  • Continuous Learning: Access to career development resources, professional growth opportunities, and internal mentorship.
  • Optimized Work Environment: Supportive, well-equipped workspaces—whether remote or in-office—designed to help you do your best work.
  • Comprehensive Wellbeing Support: Medical and retirement benefits based on location, along with mental health resources, employee assistance programs, and affinity groups.


Machine Learning Engineering Manager | Computer Vision | Deep Learning | Python | C++ | London, Hybrid

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.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.