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

Apply Now

Machine Learning Engineer

CipherTek Recruitment
London
6 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer (Databricks)

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Job Title: Machine Learning Operations Lead- Investment Banking

Location:Remote (London City- UK based) Very flexible working arrangements

Salary:£120-£150k base, 20% bonus, 13% pension + benefits

Industry: Investment Banking/Finance Technology


We are partnering with a prestigious investment bank to find a highly skilled andHands-onMachine Learning Operations(MLOps) Lead.This role will be pivotal in building out a greenfield framework for the deployment and management of scalable AI/ML solutions, specifically for the front and Middle Office user base.


The role is todefine and set up a greenfield standardized MLOps framework for capital marketsand set up all the tools and best practices to educate data scientists and equip them with the right tools and expertise. You MUST be hands on.


A strong understanding ofDevops, Machine learning and Data engineeringis required to enable to right candidate to implement the MLOps processes.


This team are a specialist team and this role in particular is a key position. Once the framework is established , you will become the gatekeeper to lots of other divisions within the bank, who will leverage your knowledge and expertise. As such, you will gain exposure to lots of different business areas and business stakeholders, so relationship building and good communication will be key.


You will bring a expertise in data science or data engineering, with a specificfocus on MLOps for at least 2 years. This platform is critical and will be rolled out across the bank, so we are looking for only the highest calibre candidates with experience building and being responsible for greenfield MLOps pipelines that handle very large datasets. You will be responsible for building out a greenfield standaridised framework for Capital markets.


The core platform is built on Azure Databricks Lakehouse, consolidating data from various front and Middle Office systems to support BI, MI, and advanced AI/ML analytics. As a lead, you will shape the MLOps framework and establish best practices for deploying and managing AI/ML solutions for a diverse and dynamic user base, including data scientists, quants, risk managers, traders, and other tech-savvy users.


Core Responsibilities:

  • Lead the development of AI/ML CI/CD pipelines and frameworks for supporting AI/ML and Data Science solutions on Azure Databricks.
  • Define and implement best practices for DataOps, DevOps, ModelOps, and LLMOps to standardize and accelerate the AI/ML life cycle.
  • Collaborate with Data Scientists and teams across Front Office Quant teams, Sales/Trading desks to build, monitor, and maintain AI/ML solutions.
  • Adopt cutting-edge advancements in GenAI and LLM technologies to keep the platform at the forefront of innovation.
  • Align with the bank's central Enterprise Advanced Analytics & Artificial Intelligence group to ensure alignment with organizational goals, strategies, and governance.
  • Manage large datasets and support data preparation, integration, and analytics across various data sources (orders, quotes, trades, risk, etc.).


Essential Requirements:

  • 2+ years of experience in MLOps and at least 3 years in AI/ML engineering.
  • Knowledge in Azure Databricks and associated services.
  • Proficiency with ML frameworks and libraries in Python.
  • Proven experience deploying and maintaining LLM services and solutions.
  • Expertise in Azure DevOps and GitHub Actions.
  • Familiarity with Databricks CLI and Databricks Job Bundle.
  • Strong programming skills in Python and SQL; familiarity with Scala is a plus.
  • Solid understanding of AI/ML algorithms, model training, evaluation (including hyperparameter tuning), deployment, monitoring, and governance.
  • Experience in handling large datasets and performing data preparation and integration.
  • Experience with Agile methodologies and SDLC practices.
  • Strong problem-solving, analytical, and communication skills.


Why Join Us?

  • Work on a greenfield project with a major global investment bank.
  • Gain deep expertise in MLOps, Azure Databricks, GenAI, and LLM technologies.
  • Play a key role in building scalable AI/ML solutions across Capital Markets.
  • Remote work flexibility with a competitive day rate.


If you are a talented MLOps professional with the expertise to help build and scale advanced AI/ML solutions in the investment banking space, we'd love to hear from you. Apply now!


How to Apply:

If you meet the qualifications and are excited about this opportunity, please submit your CV.

We look forward to hearing from you!


Job Title: Machine Learning Operations Lead- Investment Banking

Location: Remote (London City- UK based) Very flexible working arrangements

Salary: £120-£150k base, 20% bonus, 13% pension (Outside IR35)

Industry: Investment Banking/Finance Technology

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.