Senior ai/ml engineer Work, Jobs in Belgravia, Gtl (with Salaries)

Senior AI Engineer
Reward Gateway —London
- £80,000 - £90,000 a year
- Full-time
- Hybrid work
- Master's degree
- AWS
- AI
3d
Senior AI Engineer - Legal AI
9fin —London
- Full-time
- Hybrid work
- AWS
- AI
- Python
- Sick pay
Senior AI Engineer
Xelix —London
- £80,000 - £90,000 a year
- Full-time
- Hybrid work
- System design
- Master's degree
- Machine learning
- Annual leave
- Employee discount
Quick apply
Senior AI Engineer
Bluefish AI —London
- Remote
- Master's degree
- Analysis skills
- Machine learning
Senior AI Engineer (Remote)
Softblues —London
- Remote
- Azure
- English
- AWS
- Annual leave
- Flexible schedule
Senior AI Engineer - AI Transformation
Multiverse —London
- Full-time
- Hybrid work
- Product management
- APIs
- IT
- Gym membership
- Life insurance
Quick apply
Senior AI/ML Engineer
Limbic —London
- Full-time
- Hybrid work
- Azure
- Doctoral degree
- Engineering
- Annual leave
Senior Research Engineer
Decagon —London
- £200,000 - £300,000 a year
- Full-time
- AI
- Python
- Life insurance
AI Engineer, Senior Associate
Partners Capital —London
- Azure
- Computer Science
- Master's degree
- Life insurance
AI Engineering Lead
Normal Computing Corporation —London
- £250,000 - £340,000 a year
- Full-time
- Hybrid work
- Mentoring
- AI
- Leadership
Senior Principal AI Engineer
Expleo —London
- Azure
- AWS
- AI
Senior Principal AI Engineer
Synapri —London
- £90,000 - £120,000 a year
- Hybrid work
- Azure
- AWS
- Presentation skills
ML Research Engineer
White Circle —London
- £120,000 - £250,000 a year
- Full-time
- Hybrid work
- English
- SQL
- Python
- Relocation assistance
- Annual leave
1d
Senior AI Engineer
Zero100 —London
- Full-time
- Hybrid work
- Master's degree
- SQL
- AWS
- Life insurance
Quick apply
Senior Machine Learning Engineer
Lunio —London
- £70,000 - £90,000 a year
- Full-time
- Hybrid work
- SQL
- AWS
- Machine learning
AI Senior Principal Engineer
CBRE —London
- Full-time
- Master's degree
- SQL
- AWS
Multimodal ML Engineer
White Circle —London
- £120,000 - £250,000 a year
- Full-time
- Hybrid work
- APIs
- Relocation assistance
- Annual leave
1d
Senior ML Engineer
Fractal Analytics —London
- Full-time
- System design
- Analysis skills
- Machine learning
ML Infrastructure Engineer
White Circle —London
- £180,000 - £350,000 a year
- Full-time
- Hybrid work
- English
- Master's degree
- C++
- Relocation assistance
- Annual leave
1d
Senior Data Engineer
ApprovalMax —London
- £85,000 - £95,000 a year
- Remote
- Azure
- Master's degree
- SQL
- Annual leave

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Senior AI Engineer

Reward Gateway -
London

Apply Now

Job details

Full-time
£80,000 - £90,000 a year
3 days ago

Qualifications

Law
Kubernetes
Master's degree
AWS
Docker
Terraform
Natural language processing
GitHub
AI
Communication skills
Python

Full job description

Reward Gateway | Edenred, is a global leader in benefits and employee engagement. We help businesses attract, engage, and retain top talent through strategic rewards, recognition, and well-being solutions.

Guided by our shared missions of 'Making the World a Better Place to Work' and 'Enriching Connections, For Good', we are committed to transforming workplaces and improving people's daily lives.

As we continue to expand our business, we have an opportunity for a Senior AI Engineer to build and optimize production AI systems. You will work on the latest third-party AI services and frameworks, implementing LLMs, RAG architectures, and agentic workflows to boost internal tools, accelerate developer productivity, and elevate customer experience. You will collaborate with senior stakeholders across Product, Operations, and Engineering, translating business requirements into well-engineered technical solutions.

Key Responsibilities

Technical Development & Execution

Build and deliver production-ready AI and Generative AI solutions using LLMs, RAG architectures, and agents
mplement and maintain retrieval pipelines using embeddings, vector databases, hybrid search, and effective chunking strategies
Develop proof-of-concepts for emerging AI technologies and assess their production viability
Write clean, maintainable code following established engineering best practices and quality standards
Use AI coding assistants such as GitHub Copilot and Claude Code to accelerate development
Participate in code reviews and architectural discussions to improve code quality and system design

Collaboration & Problem-Solving

Work closely with Product and Engineering teams to understand requirements and deliver iterative solutions
Collaborate with cross-functional partners (Security, Data, Operations) to ensure solutions meet quality, compliance, and scalability requirements
Communicate technical decisions and tradeoffs clearly with both technical and non-technical stakeholders
Contribute to improving AI development practices and tooling through feedback and suggestions

Learning & Growth

Stay current with AI/ML developments, emerging frameworks, and best practices
Learn from more experienced engineers and contribute knowledge back to the team
Participate in capability-building activities and knowledge-sharing sessions
Build expertise in production AI systems, model evaluation, and optimization techniques

Skills, Knowledge and Expertise

Essential skills

Solid software engineering experience with a focus on production Generative AI and RAG systems
Demonstrated experience building and deploying AI systems in production environments
Strong technical expertise in LLMs, RAG, prompt engineering, embeddings, and vector databases
Hands-on experience with leading LLM providers (Anthropic Claude, OpenAI, etc.)
Strong Python development skills and proficiency with AI coding assistants (Cursor, GitHub Copilot, Claude)
Production experience with AWS cloud services and familiarity with containerization (Docker, Kubernetes)
Solid understanding of ML fundamentals, model evaluation, and performance optimization
Good communication skills with ability to collaborate effectively across teams
Data engineering capability, including working with datasets, ETL pipelines, and metrics definition

Nice to have (but not essential)

Experience with agentic workflow systems and complex orchestration patterns
Background in NLP or contributions to open-source AI/ML projects
Experience with model fine-tuning or custom training approaches
Familiarity with MLOps platforms and experiment tracking tools
Experience with infrastructure as code (Terraform, CloudFormation)

The Interview Process:

Phone interview with the Talent Acquisition Partner
Online meeting with the Director of AI Engineering
Virtual on-site (Three interviews: Technical, Product Team, VP Engineering)

Benefits

At Reward Gateway | Edenred we are committed to ensuring an inclusive and accessible recruitment process for all candidates. If you have any specific requirements or need reasonable adjustments at any stage of the recruitment journey, please let your Talent Acquisition Partner know. Your needs are important to us, and we want to ensure an equitable experience for every candidate.

Be comfortable. Be you.
We want every employee to feel comfortable bringing their passion, creativity, and individuality to work. We value all cultures, backgrounds, and experiences, because we believe diversity drives innovation and makes us stronger. Our approach to hiring and building teams is about more than filling roles - it’s about creating an environment where everyone can thrive, feel supported, and contribute to our mission of making the world a better place to work.

About Reward Gateway

Reward Gateway is culture and client driven. We’re obsessed with putting the “Human” in HR and are proud to have been 100% dedicated to HR for over a decade. Since 2007, we’ve been right by the side of the world’s most innovative HR people, giving them beautiful products and tools they can use to attract, engage and retain their people.

The world’s most successful companies treat their people differently. They generate stock market returns of twice their peers and they have half the employee turnover. 76% of CEOs recognize that employee engagement is vital to their success but only 24% say they have a highly engaged company. Bridging that engagement gap is what drives us.

Our Hiring Process

Stage 1:

Applied

Stage 2:

Review

Stage 3:

Final Interview

Stage 4:

Hired

Department

Engineering

Employment Type

Full Time

Location

London

Workplace type

Hybrid

Compensation

£80,000 - £90,000 / year

Reporting To

Director of AI Engineering

Apply Now

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