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

Apply Now

Senior Lead Software Engineer - Commodities E-Trading

JPMorgan Chase & Co.
London
1 year ago
Applications closed

Related Jobs

View all jobs

Principal Geospatial Data Engineer

Senior Design Engineer (NLP Products)

Senior Design Engineer (NLP Products)

Senior Data Engineer

Lead Data Engineer

Senior Data Engineer

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As a Senior Lead Software Engineer at JPMorgan Chase within the Commodities E-Trading teamyou are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

You will be working within a global team of developers, as well as working closely with front office and trading partners, to build real-time, low latency components underpinning key E-Trading workflows. 

Job responsibilities

Develops secure and high-quality production code, and reviews and debugs code written by others Drives decisions that influence the product design, application functionality, and technical operations and processes Use low-level programming techniques to produce highly optimized, low-latency trading software Analyse, identify, and debug technical issues occurring in globally deployed real-time systems Collaborate across global business and technical teams to design and deliver solutions  Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors Serves as a function-wide subject matter expert in one or more areas of focus Adds to the team culture of diversity, equity, inclusion, and respect

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts with advanced knowledge and applied experience Hands-on practical experience delivering system design, application development, testing, and operational stability Advanced in one or more programming language(s) Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines (., cloud, artificial intelligence, machine learning, mobile, Ability to tackle design and functionality problems independently with little to no oversight Advanced professional Java experience Capable of working independently as well as part of a team

Preferred qualifications, capabilities, and skills

Relevant markets experience Experience with scripting languages (eg Python) Strong Linux/Unix, and knowledge of networking topologies, TCP + UDP Low latency middleware 

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.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.