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

Apply Now

Tech Lead (Gen AI) - UK

Photon
1 year ago
Applications closed

Related Jobs

View all jobs

Tech Lead Machine Learning Engineer

Senior Machine Learning Scientist (Tech Lead) - Generative AI & Partner Intelligence

Principal Machine Learning Engineer

Senior Data Scientist - Insights

Staff Machine Learning Engineer

Engineering Program Manager, Machine Learning

Key Responsibilities: 

Lead the creation of a POC for using generative AI in software development, demonstrating its potential to improve efficiency, quality, and innovation.  Collaborate with software development teams to integrate generative AI solutions into existing workflows.  Lead and mentor a team of data engineers, providing technical guidance and fostering a collaborative team environment.  Design, develop, and implement generative AI applications using Python.  Work closely with stakeholders to understand business requirements and translate them into technical solutions.  Drive the development and execution of data engineering strategies to support business objectives.  Develop and maintain scalable data pipelines, API and model deployments, and workflows.  Communicate complex analytical findings and insights to non-technical stakeholders in a clear and concise manner.  Stay current with industry trends, best practices, and emerging technologies in data analytics, generative AI, and Python programming. 

Qualifications: 

Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.  5+ years of experience in data engineering and AI, with at least 2 years in a leadership or supervisory role.  Proficiency in Python programming and its libraries (. pandas, numpy, scikit-learn, matplotlib, seaborn).  Experience with cloud platforms (., AWS, Azure, Google Cloud) and their data analytics and AI services.  Strong understanding of statistical analysis, machine learning, and data mining techniques.  Experience with generative AI models (., GPT, GANs) and their applications in software development.  Experience with big data technologies (., Hadoop, Spark) and data visualization tools (., Tableau, Power BI) is a plus.  Solid experience with SQL and database management.  Excellent problem-solving skills and the ability to work independently and as part of a team.  Strong communication and interpersonal skills, with the ability to effectively convey technical concepts to non-technical stakeholders. 

Preferred Qualifications: 

Knowledge of data governance and data privacy regulations.  Experience in agile development methodologies. 

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.