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

Apply Now

Lead AI Engineer

SearchWorks
Newcastle upon Tyne
9 months ago
Applications closed

Related Jobs

View all jobs

Head of Data Science

Head of Data Science

Lead Data Engineer

Lead Data Engineer - Reigate

Senior Data Architect - Gen AI Engineering

Apply Now! Lead Data Engineer - Reigate...

My client are looking for a new Senior/Lead AI Engineer to join their growing team! They're an exciting early stage start-up who are revolutionising the insurance industry with AI powered technology! They have recently secured over $3,000,000 in initial funding and have a strong roadmap for the coming years.


You'll focus on Large Language Models and Natural Language Processing, leveraging your expertise to create AI-powered solutions that drive efficiency and accuracy.


Responsibilities:

  • Design and build AI solutions using state-of-the-art technologies.
  • Optimize AI models for specific applications and evaluate their performance.
  • Develop and maintain data pipelines for model training and inference.
  • Collaborate with engineers and product teams to integrate AI into products.
  • Stay updated on AI advancements and contribute to the company's AI strategy.


Qualifications:

  • At least 4 years of experience in AI/ML engineering, with a focus on NLP and LLMs.
  • Strong programming skills in Python and data science libraries.
  • Expertise in working with Large Language Models.
  • Experience with AI frameworks and techniques (e.g., PyTorch, RAG, Agentic architectures).
  • Knowledge of cloud-based AI services and API integrations.
  • Familiarity with data pipelines and ETL processes.
  • Experience deploying AI models in production environments.
  • Strong problem-solving and communication skills.
  • Passion for AI and its applications.
  • Strong experience within Start-Ups and Early stage companies

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.

Jobs

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

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Jobs

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Jobs

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.