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

Apply Now

Machine Learning Engineer - Computer Vision

Datatech Analytics
London
9 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer - Computer Vision
Salary negotiable dep on exp £60,000 - £80,000
Full time hybrid working - 1 or 2 days in London offices
Job Reference J12902

Full UK working rights required - no sponsorship available

Description:
Our client is an award-winning, online-only platform. Founded in 2017, they are now valued at over $1 billion and backed by some of the world's leading technology investors, having raised £143 million in Series C funding. This is a unique opportunity to join a fast-growing scale-up at a crucial phase of growth and help change an industry for the better.

About the role:
They are looking for an enthusiastic Machine Learning Engineer to join their Machine Vision team. This role focuses on developing high-quality, performant computer vision models and pushing boundaries by building innovative GenAI applications. You will be joining a team whose mission is to streamline profiling and transform the online selling and buying experience for all customers, including both sellers and dealers.

In this role, you'll collaborate closely with machine learning engineers, backend engineers, and product managers to develop scalable, high-performing ML solutions that elevate the customer journey. By applying your expertise in computer vision and exploring advanced Gen AI technologies, you'll create new applications that elevate the process for everyone involved.

Key Responsibilities:

  1. Contribute to the development, deployment, and maintenance of computer vision models in production environments, ensuring optimal performance, reliability, and scalability.
  2. Develop and implement best practices for MLOps, including version control, CI/CD pipelines, containerisation, and cloud-based orchestration.
  3. Experience in developing and shipping GenAI solutions utilising Large Language Models (LLMs).
  4. Collaborate cross-functionally: Work closely with data analysts, product managers, and business stakeholders to translate business needs into technical solutions.
  5. You have experience in, and a passion for, mentoring other ML practitioners, sharing knowledge and raising the technical bar across the team.
  6. Innovate! You'll have a keen passion for staying updated with the rapidly evolving machine learning landscape, identifying and adopting new techniques, tools, and methodologies as appropriate.


Requirements:

  1. Strong programming skills in Python and good experience with machine learning libraries such as PyTorch (preferable), TensorFlow.
  2. Experience in deploying, maintaining, and optimising deep learning pipelines, focusing on efficiency, performance, and production maturity.
  3. Strong understanding of machine learning principles, deep learning techniques and concepts such as prompt engineering, chain-of-thought reasoning, prompt chaining, Retrieval-Augmented Generation (RAG), custom-built agents.
  4. Familiarity with LLM frameworks like LangChain, AutoGen, or similar.
  5. Proficiency in ML-Ops practices and tools; basic understanding of DevOps and CI/CD.
  6. Experience with cloud platforms (e.g. AWS, GCP) and deploying models in production.
  7. Proficient in Docker and cloud-based container orchestration services such as AWS Fargate, Google Cloud Run etc.
  8. You thrive working on ambiguous problems and have a track record of helping your team and stakeholders resolve ambiguity.
  9. You're excited about fast-moving developments in Machine Learning and can communicate those ideas to colleagues who are not familiar with the domain.


We encourage you to apply, even if you don't consider you have all the skills required!

Equal opportunities statement:
They are committed to equality of opportunity for all employees. They work to provide a supportive and inclusive environment where people can maximise their full potential. They believe their workforce should reflect a variety of backgrounds, talents, perspectives and experiences. Their strong commitment to a culture of inclusion is evident through their constant focus on recruiting, developing and advancing individuals based on their skills and talents.

They welcome applications from all individuals regardless of age, disability, sex, gender reassignment, sexual orientation, pregnancy and maternity, race, religion or belief and marriage and civil partnerships.

If this sounds like the role for you then please apply today!#J-18808-Ljbffr

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 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.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.