RELX on cord

RELX

Machine Learning Engineering Lead

External position
Farringdon, UK
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Data · Publishing
RELX is a global provider of information-based analytics.
Posted
2 weeks ago
Checked
cord regularly checks that external positions are still open
2 hours ago

Skills & Experience

Job roles: Machine Learning Engineer
Experience level: Lead
Core skills considered: Python, Machine Learning, AWS, CI/CD, Automated Testing
Other skills considered: Docker, Kubernetes, Terraform, Technical Writing

Logistics

Base salary: Undisclosed
Some companies on cord are unable to disclose salaries publicly due to internal company policies. Message the company for salary information.
Employment type: Permanent
Remote working: On-site
Visa sponsorship: Not available

Job Description

This position serves as a subject matter expert for Machine Learning Engineering, supporting production AI/ML, LLM/RAG, and agentic workflow capabilities for legal content products. In addition to writing code on complex systems, this position provides technical direction on architecture, MLOps, responsible AI, legacy system integration, AWS-based delivery, and AI-assisted development practices. The position does not have direct reports.


Key Responsibilities:

  • Serve as the initial point of escalation for AI/ML engineering issues within the area of responsibility.
  • Interface with software engineers, data engineers, product stakeholders, domain experts, platform teams, and other technical personnel to finalise requirements and clarify integration needs.
  • Write and review portions of detailed specifications for the development of complex AI/ML, LLM, RAG, and agentic workflow components.
  • Design, build, integrate, deploy, and operate production AI/ML and LLM-based services for legal research, analytics, and content use cases.
  • Implement RAG, semantic search, embeddings-based retrieval, ranking, summarisation, classification, content enrichment, and citation-aware AI capabilities where appropriate.
  • Design and implement agentic workflows, tool orchestration, and multi-step AI processes that are reliable, traceable, and governed.
  • Integrate AI/ML capabilities with enterprise systems, APIs, databases, data platforms, content repositories, legacy applications, internal services, and AWS-hosted services.
  • Establish evaluation and quality controls for accuracy, groundedness, citation quality, hallucination risk, agent task success, latency, cost, reliability, and business value.
  • Successfully implement development processes, coding best practices, code reviews, MLOps practices, and responsible AI controls.
  • Apply AI-assisted development tools to reduce software development cycle time and support code explanation, test generation, refactoring, debugging, documentation, code review, migration planning, and legacy system analysis.
  • Resolve complex technical issues related to AI/ML services, data flows, system integration, model behaviour, production support, and operational reliability.
  • Mentor and/or train engineers as directed by department management, ensuring they are knowledgeable in critical aspects of AI/ML engineering, MLOps, SDLC practices, and responsible use of AI-assisted development tools.
  • Keep abreast of relevant technology developments in machine learning engineering, LLMs, agentic workflows, AWS cloud services, responsible AI, and software engineering practices.
  • Ensure AI/ML solutions align with enterprise data governance, security, privacy, responsible AI, and operational standards.
  • All other duties as assigned.

Requirements:


Qualifications -

  • Significant hands-on experience in machine learning engineering, software engineering, data engineering, or a related technical discipline.
  • Experience designing, building, deploying, and operating ML, AI, LLM, or data-driven systems in production.
  • Experience integrating AI/ML services with enterprise systems, APIs, databases, data platforms, legacy applications, or internal services.
  • Experience working with cross-functional teams to understand business processes, data flows, content repositories, integration points, and operational constraints.
  • Experience working with AWS or cloud-hosted production environments.
  • Equivalent technical experience or education considered.

Technical Skills-

  • Strong Python development skills for machine learning engineering, data processing, automation, service development, and production AI/ML workflows.
  • Strong software engineering background, including system design, APIs, distributed systems, automated testing, code review, maintainability, reliability, and production support.
  • Strong understanding of ML engineering and MLOps practices, including model lifecycle management, CI/CD, testing, monitoring, release management, observability, and operational support.
  • Practical experience with LLM-based capabilities, including retrieval-augmented generation, semantic search, embeddings, prompt design, evaluation, guardrails, and observability.
  • Experience with agentic workflows, tool orchestration, and multi-step AI processes.
  • Strong AWS knowledge, including cloud-hosted applications, data services, security controls, logging, monitoring, and production support.
  • Strong understanding of SDLC practices, including requirements analysis, design, implementation, automated testing, code review, secure coding, deployment, and production support.
  • Strong understanding of responsible AI practices, including evaluation, traceability, secure data handling, model governance, human oversight, and risk management.
  • Ability to work with structured, semi-structured, and unstructured data sources.
  • Ability to understand legacy systems, domain processes, data flows, and integration constraints.
  • Practical experience using AI-assisted development tools such as GitHub Copilot, Codex, Claude, or similar tools to improve software delivery.
  • Strong problem-solving skills, including identifying, researching, troubleshooting, and resolving complex technical, data, and integration issues.
  • Strong communication and technical writing skills, including the ability to explain ML and engineering concepts clearly to technical and non-technical stakeholders.
  • Desirable experience with Docker, Kubernetes/K8s, AWS EKS or ECS, Terraform, or similar cloud deployment technologies.
  • Desirable working knowledge of C#/.NET and SQL Server, particularly for integration with enterprise or legacy systems.
  • Desirable experience with event-driven architecture, messaging, queues, asynchronous processing, retries, idempotency, and failure handling.
  • Desirable experience with legal content systems, LegalTech, publishing platforms, case law, citation systems, legal research workflows, XML/XSLT, structured content processing, search, ranking, indexing pipelines, or content enrichment.

Company Benefits

  • 25 days holiday.
  • 2 paid charity days a year (as a business we do a lot of charity work)
  • Pension and life assurance schemes
  • Save As You Earn Share Scheme (SAYE).
  • Competitive Salaries.
Machine Learning Engineering Lead at RELX
Position posted 2 weeks ago

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Starling Bank on cord

Starling Bank

Full Stack Engineer (ML Ops)

London, UK
FinTech · Banking · Finance
A better bank for everyone
Active
over 6 months ago
Responds to
0% of requests
Responds in
1h 55m
Requests
7 pending

Skills & Experience

Job roles: Full Stack
Experience level: Mid, Senior
Core skills considered: Java, React, Redux, AWS, JavaScript

Logistics

Base salary: £70K - £110K
Employment type: Permanent
Remote working: Hybrid (up to 2 remote days p/w)
Visa sponsorship: Not available

Job Description

Starling is the UK’s first and leading digital bank on a mission to fix banking! Our vision is fast technology, fair service, and honest values. All at the tap of a phone, all the time.

Starling is the UK’s first and leading digital bank on a mission to fix banking! We built a new kind of bank because we knew technology had the power to help people save, spend and manage their money in a new and transformative way.

We’re a fully licensed UK bank with the culture and spirit of a fast-moving, disruptive tech company. We’re a bank, but better: fairer, easier to use and designed to demystify money for everyone. We employ more than 3,000 people across our London, Southampton, Cardiff and Manchester offices.

Our technologists are at the very heart of Starling and enjoy working in a fast-paced environment that is all about building things, creating new stuff, and disruptive technology that keeps us on the cutting edge of fintech. We operate a flat structure to empower you to make decisions regardless of what your primary responsibilities may be, innovation and collaboration will be at the core of everything you do. Help is never far away in our open culture, you will find support in your team and from across the business, we are in this together!

The way to thrive and shine within Starling is to be a self-driven individual and be able to take full ownership of everything around you: From building things, designing, discovering, to sharing knowledge with your colleagues and making sure all processes are efficient and productive to deliver the best possible results for our customers. Our purpose is underpinned by five Starling values: Listen, Keep It Simple, Do The Right Thing, Own It, and Aim For Greatness.

Hybrid Working

We have a Hybrid approach to working here at Starling - our preference is that you're located within a commutable distance of one of our offices so that we're able to interact and collaborate in person. We don't like to mandate how much you visit the office and work from home, that's to be agreed upon between you and your manager.

Our Data Environment

Our Data teams are excited about the value of data within the business, powers our product decisions to improve things for our customers and enhance effective and agile decision making, regardless of what their primary tech stack may be. Hear from the team in our latest blogs or our case studies with Women in Tech.

We are looking for talented data professionals at all levels to join the team. We value people being engaged and caring about customers, caring about the code they write and the contribution they make to Starling. People with a broad ability to apply themselves to a multitude of problems and challenges, who can work across teams do great things here at Starling, to continue changing banking for good.

Requirements

We have built our entire banking platform in house and mostly in Java. We are looking for people who want to work on building the tooling that is used by our engineers on a daily basis.

We are looking for people who are truly full stack, and are as comfortable polishing their javascript front end as they are debugging the innards of their java applications database interactions, or standing up infrastructure with terraform. We are looking for people who can:

  • Design REST apis.
  • Code backend services, ideally using Java, or another other server side compiled language.
  • Develop modern front ends, ideally using React and Redux.
  • Get their code into the cloud and support it there, ideally on AWS.
  • Believe in clean coding, simple solutions, automated testing and continuous deployment.
  • Like to take ownership of a feature from the original idea through to live.
  • Think (like us) that a small number of empowered developers is the right way to deliver software.

Company Benefits

  • 33 days holiday (including flexible bank holidays)
  • An extra day’s holiday for your birthday
  • 16 hours paid volunteering time a year
  • Part-time and/or flexible hours available for most roles
  • Salary sacrifice, company enhanced pension scheme
  • Life insurance at 4x your salary
  • Hybrid/remote working
  • Private Medical Insurance with VitalityHealth including mental health support and cancer care. Partner benefits include discounts with Waitrose, Mr&Mrs Smith and Peloton
  • Generous family-friendly policies
  • Varied social groups set up and run by our employees
  • Perkbox membership giving access to retail discounts, a wellness platform for physical and mental health, and weekly free and boosted perks
  • Access to initiatives like Cycle to Work, Salary Sacrificed Gym partnerships and Electric Vehicle (EV) leasing

Full details are available on our careers site

Interview Process

Interviewing is a two way process and we want you to have the time and opportunity to get to know us, as much as we are getting to know you! Our interviews are conversational and we want to get the best from you, so come with questions and be curious. In general you can expect the below, following a chat with one of our Talent Team:

  • Stage 1 - 30 mins with one of the team
  • Stage 2 - Take home challenge
  • Stage 3 - 90 mins technical interview with two team members
  • Stage 3 - 45 min final with an executive and a member of the people team
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