Gen AI Specialist

CV-Library
London
12 months ago
Applications closed

Related Jobs

View all jobs

GenAI/ML Principal Sales Specialist, UKI AI Specialist Team

Amazon London, United Kingdom
Permanent

CMC Project Lead (Next Generation Biologics and ADCs), London

Isomorphic Labs London, United Kingdom

Associate Professional Services Consultant Intern 2026

Amazon London, United Kingdom
Permanent

Partner AI Deployment Engineer - AWS

OpenAI London, United Kingdom
Permanent

AI Engineer - FDE (Forward Deployed Engineer)

Databricks London, United Kingdom

Data Scientist - Gen AI

Vallum Associates Sheffield, South Yorkshire, United Kingdom
£525 – £550 pd
Posted
17 Apr 2025 (12 months ago)

Gen AI Specialist
Location: Canary Wharf, London (3 days onsite)
Contract Length: 10 months
Daily Rate: £800 - £850 (inside IR35 via umbrella)

Are you a seasoned Data Scientist with a passion for Generative AI? Our client is seeking a Gen AI Specialist to join their dynamic Technology team in Canary Wharf. This role offers an exciting opportunity to work on innovative solutions that address complex financial data challenges, particularly in credit risk management.

Key Responsibilities:

Lead the development and coordination of analytical plans, ensuring alignment with various teams.
Manage deliverables in an agile environment while maintaining clear and effective communication with stakeholders.
Present analytical findings, updates, and challenges to diverse audiences including business units, technology management, and risk review teams.
Execute data modelling and cleaning processes utilising both internal and external data sources.
Build predictive and prescriptive models through data manipulation and cleaning.
Design, manage, and deploy analytical solutions leveraging Machine Learning (ML), Deep Learning (DL), and Large Language Models (LLMs) into production systems following the technology SDLC process.
Implement features throughout the ML lifecycle-Development, Testing, Training, Production, and Monitoring-to ensure the scalability and reliability of solutions.Qualifications:

PhD or master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
Minimum of 5 years of industry experience as a data scientist, with a focus on ML modelling, Ranking, Recommendations, or Personalization systems.
Proven track record of designing and developing scalable and reliable machine learning systems.
Strong expertise in ML/DL/LLM algorithms, model architectures, and training techniques.
Proficiency in programming languages such as Python, SQL, Spark, PySpark, TensorFlow, or equivalent analytical/model-building tools.
Familiarity with tools and technologies related to LLMs.
Ability to work independently while also thriving in a collaborative team environment.
Experience with GenAI/LLMs projects.
Familiarity with distributed data/computing tools (e.g., Hadoop, Hive, Spark, MySQL).
Background in financial services, including banking or risk management.
Knowledge of capital markets and financial instruments, along with modelling expertise.

If you are a forward-thinking individual with an adaptive mindset ready to tackle complex business problems, we want to hear from you! Join our client's innovative team and contribute to the future of financial data analysis.

To Apply: Please submit your CV and a cover letter detailing your relevant experience and interest in the role.

Our client is an equal opportunity employer and welcomes applicants from diverse backgrounds.

Adecco is a disability-confident employer. It is important to us that we run an inclusive and accessible recruitment process to support candidates of all backgrounds and all abilities to apply. Adecco is committed to building a supportive environment for you to explore the next steps in your career. If you require reasonable adjustments at any stage, please let us know and we will be happy to support you

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.

Where to Advertise Machine Learning Jobs in the UK (2026 Guide)

Advertising machine learning jobs in the UK requires a different approach to most technical hiring. The candidate pool is small, highly specialised and in demand across AI labs, financial services, healthcare, autonomous systems and consumer technology simultaneously. Machine learning engineers and researchers move between roles through professional networks, conference communities and specialist platforms — not general job boards where ML roles compete with unrelated software engineering positions for the same audience. This guide, published by MachineLearningJobs.co.uk, covers where to advertise machine learning roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.