Senior Java Developer - Artificial Intelligence

Client Server
London
1 year ago
Applications closed

Related Jobs

View all jobs

Staff Data Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer - Research

Senior Data Scientist

Senior Data Engineer

Senior Data Engineer (AWS, Airflow, Python)

Senior Java Developer / Software Engineer (Java SpringBoot AI) London to £95k

Are you a technologist Java Developer with experience of working on cutting edge Artificial Intelligence?

You could be progressing your career in a hands-on leadership role at one of the country's leading PropTech sites that have revolutionised the way we find property for rent and sale with millions of users per day.

As a Senior Java Developer you'll join a cross functional team, collaborating with Data Scientists and Machine Learning Engineers as the business seeks to introduce cutting edge AI technology. You'll design and implement the underlying application layer to expose and encapsulate fundamental Generative AI capabilities, facilitating scalability and the adoption of AI including AI systems and architecture, prompt engine development, continuous monitoring and evaluation.

You will act as an AI champion within the wider technology team, keeping up with the latest advancements, seeking continual improvement and providing mentoring to other engineers as a valued member of the company's tech community.

Location / WFH:

You'll join colleagues in the Central London office for two days a week with flexibility to work from home the other three days.

About you:

You have commercial experience of working with AI, a demonstratable interest in Generative AI concepts such as LLM, OpenAI, Hugging Face, Vision, multi-modal, embedding models, similarity search, dense vector persistence as well as an understanding of Machine Learning concepts - you may have an relevant MSc, contribute to blogs, attend conferences and events You have strong backend web development experience with Java and SpringBoot You have technical project leadership and mentoring experience You have experience with RESTful APIs, messaging, event souring; Kafka would also be nice You have a test driven approach, TDD, Agile methodologies and processes You have strong analysis, problem solving and critical thinking skills

What's in it for you:

Salary to £95k Pension Private healthcare including optical and physio Life Assurance Enhanced maternity / paternity packages Travel loan and cycle to work scheme Savings schemes Tax free charity donations Hybrid working (x2 days a week in London) Opportunity to work on AI technology with excellent career growth

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.

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.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.