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

Apply Now

Digital Audit - Senior Associate - Gen AI Pod

PwC
London
1 year ago
Applications closed

Related Jobs

View all jobs

Assistant Manager- Algorithm & Artificial Intelligence (AI) Assurance - Audit & Assurance

Computer Vision Tech Lead

Data Scientist – Fraud Strategic Analytics Lead

Lead Machine Learning Engineer

Senior Data Scientist

Machine Learning Engineer – AI Team (Global Digital)

The Role

 

At the GenAI Pod, we’re pushing the boundaries of what’s possible. As a Senior Associate in our GenAI Lab start-up, you will:

Pioneer the design, development, and deployment of production machine learning pipelines

Shape machine learning-enabled, Audit applications

Deliver high-quality code contributions to our evolving codebase

Monitor and review live production models

Lead and guide workstreams on projects within your specialisation

Mentor and manage junior engineers on impactful workstreams

Skills and Experience

A passionate data scientist, who has invested time in understanding Generative AI and experienced the power of LLM

Practical experience from industry and professional services in delivering significant and valuable advanced analytics projects and/or assets

Engagement of technical and senior stakeholders

Ability to manage and coach a team of data scientists

Delivery of projects on time and in budget for high profile clients

Understanding of requirements for software engineering and data governance in data science

We make extensive use of the following technologies in our team. We expect you to be fluent with using these tools and practices on a daily basis.

Bachelor's degree (or more) in computer science / Data Science or a related technical discipline

Experience in Natural Language Processing

Extensive experience with modern Deep Learning (PyTorch/TensorFlow)

Experience with any of the following NLP tasks - named entity recognition, intelligent document processing, website parsing & classification, sentiment analysis, information retrieval, entity matching & linking, spelling correction

Strong knowledge of Mathematical Statistics, Algorithms & Data Structures, ML Theory

Strong knowledge of Python & SQL

Strong debugging skills

Git for version control

Azure / GCP for our cloud backend

Skills we’d like to hear about

Experience working with large data pipelines (using technologies such as Beam or Kafka)

Experience in LLMs using OpenAI, Gemini or open source models

Exposure to other programming languages (such as Java)

Experience of working on a project using agile concepts (such as working in sprints)

Familiarity with working in an MLOps environment.

Experience working with search engines (such as Elasticsearch)

)


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.

AI Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we head into 2026, the AI hiring market in the UK is going through one of its biggest shake-ups yet. Economic conditions are still tight, some employers are cutting headcount, & AI itself is automating whole chunks of work. At the same time, demand for strong AI talent is still rising, salaries for in-demand skills remain high, & new roles are emerging around AI safety, governance & automation. Whether you are an AI job seeker planning your next move or a recruiter trying to build teams in a volatile market, understanding the key AI hiring trends for 2026 will help you stay ahead. This guide breaks down the most important trends to watch, what they mean in practice, & how to adapt – with practical actions for both candidates & hiring teams.

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.