1,334 Tensorflow jobs in the United Kingdom

Role Purpose & Projects

This is a hybrid role where you'd be required in the Glasgow office 2 days per week. 1 day per week may be considered for candidates in outlying areas.

This team is responsible for designing and delivering AI-enabled software solutions that enhance workflows and improve efficiency across the business. Projects include:

• Building AI applications and internal tooling
• Automating workflows and documentation (e.g. technical content, training manuals)
• Integrating AI agents into applications
• Example: AI chatbot leveraging orchestration frameworks and APIs (OpenAI, Perplexity, Google)
• Tools and solutions for Sales, Marketing, and Engineering functions

This is not a pure data science or ML model training role —the focus is on AI-driven software development and automation .

Skills & Experience

Essential:

• 5–6 years’ experience as a software engineer in an enterprise setting
• Strong C# / .NET development background
• Experience with Azure (hosting, deploying, Azure Functions)
• Experience building CI/CD pipelines
• Frontend experience with React

Preferred:

• Exposure to tools like GitHub Copilot
• Knowledge of AI orchestration frameworks (Semantic Kernel, LangChain, LangGraph )
• Experience integrating LLMs (OpenAI, Perplexity, Google APIs)
• Demonstrated personal AI projects or a strong motivation to upskill in AI

Candidate Profile

• Strong software engineer with proven experience building enterprise-grade applications
• Hands-on AI experience or keen interest in applying AI in real-world settings
• Comfortable working in a small, fast-moving team building tools from scratch
• Enterprise mindset: security, scalability, and quality at the core of delivery

Compensation & Level

• Multiple levels available, with a preference for senior-level hires
• Competitive salary + bonus + benefits
• Visa sponsorship available

Senior AI Software Engineer

London

£90,000-£130,000

I’m partnering with a dynamic AI consultancy that embeds itself within client businesses, listening closely, then building bespoke agentic AI solutions that automate processes, improve speed, and enhance decision-making.

Role Responsibilities

As a Senior AI Applied Engineer, you will:

• Build & Deploy AI-Driven Software Solutions
• You’ll blend software engineering and AI expertise to develop scalable, production-grade systems leveraging generative AI and agentic automation.
• Own Project-Based Work Across Diverse Domains
• You’ll tackle varied engagements, ranging in length and complexity, and support multiple clients.
• Ensure Scalable and Reliable Deployment
• Your role includes end-to-end responsibility for deploying AI solutions that are robust, maintainable, and optimized for performance at scale.
• Act as a Strong Team Contributor and Communicator
• While you won’t lead client engagements, you’ll work closely with clients and internal teams, translating client needs into technical solutions, requiring strong communication and stakeholder-facing capabilities.
• Leverage Generative AI Expertise
• Utilise your hands-on experience with generative AI tools or workflows, prompt engineering, LLM integration, or similar, but the emphasis is on engineering implementation and delivery.

Who We're Looking For

Essential Qualifications & Experience

• Strong software engineering background with deep experience deploying scalable systems
• At least some commercial experience using Generative AI exposure (e.g., LLMs, agentic interfaces, prompt engineering) but primarily strong engineering fluency
• Comfortable with project-based, delivery-focused work, even if no prior consultancy experience
• Confident in client-facing situations and able to collaborate effectively with non-technical stakeholders
• Reliable, consistent work history; this is a long-term growth-focused opportunity within an expanding team

Ready to Apply?

If this resonates with your background and career path, let’s talk. Please share your CV highlighting your engineering experience and where generative AI has featured, especially in deployment or integration roles.

Contract AI Engineer – Azure AI Agents | Inside IR35 | Hybrid (UK-based)

Join one of the UK’s leading Investment management firms' cutting-edge AI transformation project. They're building a Greenfield AI agent platform to revolutionise how investors interact with customer data.

What You’ll Do

• Build and deploy modular AI agents using Python and containerisation tools.
• Leverage RAG, embeddings, and OCR to synthesise customer data.
• Collaborate with data engineers, DevOps, and integration specialists.
• Deliver APIs for seamless integration into Microsoft 365 and Dynamics 365 environments.
• Contribute to a high-impact roadmap with full business support.

What You’ll Bring

• Proven experience shipping production AI solutions.
• Strong Python and containerisation skills (Azure Container Apps, Kubernetes, etc.).
• Familiarity with multi-agent orchestration frameworks (e.g., Semantic Kernel, Autogen, Azure Agentic).
• Experience with Azure integration services is a bonus.
• Passion for AI and automation - financial services background not required.

Why Join?

• Greenfield opportunity in a highly supportive environment.
• Exposure to cutting-edge AI tooling and real-world customer data.
• Flexible team, open to mid-level engineers with strong delivery experience.
• Initial 6-month contract with potential for extension.

Job Title: AI Researcher

Location: Cambridge or London, UK

This is a permanent position with candidates required to do hybrid working in either Cambridge or London.

Our client are looking for AI Researchers specialising in Reinforcement Learning with Human Feedback (RLHF) and Generative AI. In this role, you will design and optimise the algorithms that align large-scale generative models with human preferences, ensuring they are safe, controllable, and capable of producing high-quality outputs across multiple modalities. You’ll sit at the intersection of RL, LLMs, and generative modelling, helping us build the next generation of foundation models

Responsibilities:

Develop and refine RLHF algorithms for large language and generative models.

Research and implement deep reinforcement learning methods (policy gradients, actor-critic, off-policy learning) for model alignment.

Train, fine-tune, and evaluate LLMs and diffusion models at scale.

Design experiments to align generative outputs with human and organisational preferences.

Collaborate with researchers, engineers, and human feedback teams to build scalable alignment pipelines.

Publish findings in top-tier AI conferences and contribute to open-source frameworks.

Key Requirements:

PhD in Computer Science, Machine Learning, or related field.

Publications at NeurIPS, ICML, ICLR, ACL, or related venues.

Deep expertise in Reinforcement Learning (policy optimisation, reward modelling, RLHF).

Hands-on experience training/fine-tuning generative models (LLMs, diffusion, transformers, GANs).

Strong knowledge of deep learning frameworks (PyTorch, JAX, TensorFlow).

Proficiency in Python and standard ML libraries.

Solid foundations in probability, optimisation, and statistics.

Experience working with large-scale distributed training on GPUs/TPUs.

If this sounds of interest, please reach out to

Job Title: AI Researcher

Location: Cambridge or London, UK

This is a permanent position with candidates required to do hybrid working in either Cambridge or London.

Our client are looking for AI Researchers specialising in Reinforcement Learning with Human Feedback (RLHF) and Generative AI. In this role, you will design and optimise the algorithms that align large-scale generative models with human preferences, ensuring they are safe, controllable, and capable of producing high-quality outputs across multiple modalities. You’ll sit at the intersection of RL, LLMs, and generative modelling, helping us build the next generation of foundation models

Responsibilities:

Develop and refine RLHF algorithms for large language and generative models.

Research and implement deep reinforcement learning methods (policy gradients, actor-critic, off-policy learning) for model alignment.

Train, fine-tune, and evaluate LLMs and diffusion models at scale.

Design experiments to align generative outputs with human and organisational preferences.

Collaborate with researchers, engineers, and human feedback teams to build scalable alignment pipelines.

Publish findings in top-tier AI conferences and contribute to open-source frameworks.

Key Requirements:

PhD in Computer Science, Machine Learning, or related field.

Publications at NeurIPS, ICML, ICLR, ACL, or related venues.

Deep expertise in Reinforcement Learning (policy optimisation, reward modelling, RLHF).

Hands-on experience training/fine-tuning generative models (LLMs, diffusion, transformers, GANs).

Strong knowledge of deep learning frameworks (PyTorch, JAX, TensorFlow).

Proficiency in Python and standard ML libraries.

Solid foundations in probability, optimisation, and statistics.

Experience working with large-scale distributed training on GPUs/TPUs.

If this sounds of interest, please reach out to