Software Engineer II - Java/ Spring/ Kafka

JPMorgan Chase & Co.
Glasgow
3 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Head of Software Engineering | £150k – Java, Machine Learning, and Data-Driven Innovation

Engineering Manager

Machine Learning and AI Engineering Lead

Software Engineer

Python Software engineer | 9 Months | Outside IR35 | Hybrid Bath | Data Science

You’re ready to gain the skills and experience needed to grow within your role and advance your career — and we have the perfect software engineering opportunity for you.

As a Software Engineer II at JPMorgan Chase within the Corporate Sector Credit Risk team, you are part of an agile team that works to enhance, design, and deliver the software components of the firm’s state-of-the-art technology products in a secure, stable, and scalable way. As an emerging member of a software engineering team, you execute software solutions through the design, development, and technical troubleshooting of multiple components within a technical product, application, or system, while gaining the skills and experience needed to grow within your role.

Job responsibilities

Executes standard software solutions, design, development, and technical troubleshooting Writes secure and high-quality code using the syntax of at least one programming language with limited guidance Designs, develops, codes, and troubleshoots with consideration of upstream and downstream systems and technical implications Applies knowledge of tools within the Software Development Life Cycle toolchain to improve the value realized by automation Applies technical troubleshooting to break down solutions and solve technical problems of basic complexity Gathers, analyzes, and draws conclusions from large, diverse data sets to identify problems and contribute to decision-making in service of secure, stable application development Learns and applies system processes, methodologies, and skills for the development of secure, stable code and systems Adds to team culture of diversity, equity, inclusion, and respect

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and applied experience  Hands-on practical experience in system design, application development, testing, and operational stability Extensive experience with Java and Spring Framework Experience with multi-threading Experience with Kafka and streaming technologies Experience in creating Restful web services Experience of working with RDBMS’s (Oracle) Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages Overall knowledge of the Software Development Life Cycle Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security Demonstrated knowledge of software applications and technical processes within a technical discipline (., cloud, artificial intelligence, machine learning, mobile,

Preferred qualifications, capabilities, and skills

Knowledge in Big Data development and software design Understanding of Risk Management and Credit Risk 

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Machine learning (ML) has become the beating heart of modern tech innovation, powering breakthroughs in healthcare, finance, cybersecurity, robotics, and more. Across the United Kingdom, this surge in ML-driven solutions is fueling the success of countless start-ups—and spurring demand for talented machine learning engineers, data scientists, and related professionals. If you’re eager to join a high-growth ML company or simply want to keep tabs on the latest trends, this Q3 2025 Investment Tracker will guide you through the newly funded UK start-ups pushing the boundaries of ML. In this article, we’ll highlight key developments from Q3 2025, delve into the most promising newly funded ventures, and shed light on the machine learning roles they’re urgently seeking to fill. Plus, we’ll show you how to connect with these employers via MachineLearningJobs.co.uk, a dedicated platform for ML job seekers. Let’s dive in!

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.