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

Apply Now

Lead Machine Learning Engineer (Pet care)

La Fosse
London
3 weeks ago
Applications closed

Related Jobs

View all jobs

Lead Machine Learning Engineer

Lead Machine Learning Engineer

Lead Machine Learning Engineer

Lead Machine Learning Engineer

Lead Machine Learning Engineer – Real-Time Personalization

Staff/Lead Machine Learning Engineer (CV / Research)

Lead Machine Learning Engineer (Pet care)


  • Location: London – 1/2 days a week in the office
  • Salary: Up to £90/95k + £7.5k Car allowance + 20% bonus
  • Pet care


Are you passionate about using data and technology to make a real-world difference?


Join a global leader in pet health and nutrition that’s harnessing the power of AI and machine learning to create a better world for pets — and the people who care for them. This company organisation is transforming how we understand and deliver pet wellbeing through data-driven insights.


They bring together expertise in veterinary science, nutrition, and digital innovation to improve the lives of millions of pets around the world. This is your opportunity to be part of a forward-thinking team where cutting-edge technology meets genuine purpose.


The Role:

I’m seeking a Lead Machine Learning Engineer to drive the design, deployment, and scaling of ML solutions across our global data ecosystem.

You’ll be the technical lead for machine learning and AI engineering — building production-ready systems, enabling seamless collaboration with data scientists, and shaping the long-term MLOps strategy. Beyond implementation, you’ll play a pivotal role in defining how advanced analytics supports smarter decision-making, better customer experiences, and more sustainable operations across the business.


What You’ll Do:

  • Lead the technical direction of machine learning engineering and deployment, ensuring models are robust, scalable, and high performing.
  • Work hand-in-hand with data scientists to design, prototype, and operationalize ML and AI models that deliver real business value.
  • Develop and maintain a comprehensive MLOps framework — from versioning and CI/CD to monitoring and governance.
  • Provide technical guidance and mentorship, helping grow a capable ML Engineering team over time.
  • Partner with product, platform, and analytics teams to embed ML into data products and digital services.
  • Stay current with advancements in Generative AI and LLMs, exploring opportunities to apply them within the pet care and nutrition space.


What We’re Looking For

  • Strong communicator who can translate technical complexity into business value.
  • Proven experience in classical machine learning, with hands-on expertise in model development, optimisation, and deployment.
  • Deep understanding of ML Engineering and MLOps principles (cloud-based pipelines, CI/CD, monitoring, reproducibility).
  • Experience with Python, SQL & Azure (AWS & GCP is also fine).
  • Exposure to GenAI or LLM tools and frameworks is a strong advantage.
  • Strategic thinker with the confidence to lead technically and shape the roadmap for ML within a growing, collaborative team.
  • Desire to apply technology in ways that make a tangible difference in the world of pet wellbeing and sustainability.


Why Join?

This is more than just a technical leadership role — it’s a chance to combine your passion for data with a mission that matters. You’ll be joining a diverse, global team that’s reimagining the future of pet care through data, science, and innovation.


If you’re interested in this role, please apply through the AD to find out more!


Lead 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.

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.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.