720 Machine Learning Manager jobs in the United Kingdom
Machine Learning Manager, London
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Machine Learning Manager, London
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myGwork - LGBTQ+ Business Community .nThis job advert is with Isomorphic Labs, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Isomorphic Labs is applying frontier AI to help unlock deeper scientific insights, faster breakthroughs, and life-changing medicines with an ambition to solve all disease. The future is coming, enabled by machine learning, with a focus on accelerating drug discovery. The company fosters an interdisciplinary team with a collaborative culture.nIsomorphic Labs (IsoLabs) was launched in 2021 to advance human health by building on and beyond the Nobel-winning AlphaFold system. The team develops predictive and generative AI models to accelerate scientific discovery and drug design across multiple therapeutic areas and modalities.nYour Role
Machine Learning Engineering Lead, London
— You will play a pivotal role in shaping and driving the engineering foundations that underpin an AI-first approach to drug discovery. You will lead a team of ML and full stack software engineers, guiding them in building robust, scalable, and innovative machine learning systems and infrastructure. Your work will translate groundbreaking research into tangible tools and platforms that accelerate medicine discovery. This is an opportunity to combine passion for machine learning, software engineering excellence, and leadership to impact human health.nKey Responsibilities
Technical Leadership & Vision: Provide technical direction for a team of ML, Fullstack and Backend Software Engineers. Define and drive the technical roadmap for ML systems, infrastructure, and tooling in collaboration with research scientists, ML researchers, and other engineering teams.nTeam Mentorship & Development: Mentor and grow teams of ML SWEs, Fullstack and Backend SWEs, fostering technical excellence, innovation, and collaboration. Guide on career development, best practices, and problem-solving.nML System Design & Implementation: Lead design, development, deployment, and maintenance of scalable, production-ready ML models, pipelines, and platforms, including data ingestion, preprocessing, model training, evaluation, serving, and monitoring.nSoftware Engineering Excellence: Champion best practices in software engineering, including code quality, testing, CI/CD, version control, documentation, and infrastructure as code. Ensure high-quality, maintainable, and efficient software.nCross-Functional Collaboration: Work with AI researchers, biologists, chemists, and engineers to translate research ideas into production systems and apply ML to complex scientific challenges.nInnovation & Problem Solving: Stay at the forefront of ML, MLOps, and software engineering. Evaluate new technologies to enhance capabilities for drug discovery.nProject Management & Execution: Oversee complex ML engineering projects, ensuring timely delivery and alignment with goals. Manage priorities, resources, and timelines.nOperational Excellence: Ensure reliability, scalability, and efficiency of ML systems in production. Implement monitoring, alerting, and incident response processes.nSkills and qualifications
Essential :nDemonstrable experience in an ML engineering leadership or management role, including mentoring and guiding engineering teams.nProven software engineering experience with a strong focus on machine learning.nStrong proficiency in Python and ML libraries/frameworks (e.g., TensorFlow, PyTorch, JAX, scikit-learn).nSolid understanding of ML concepts, algorithms, and best practices (deep learning, reinforcement learning, generative models, MLOps).nExperience designing, building, deploying scalable ML systems in production (cloud platforms such as GCP, AWS, or Azure).nExcellent software engineering fundamentals (data structures, algorithms, design patterns, distributed systems).nExperience with MLOps tools (e.g., Kubeflow, MLflow, Airflow) and ML-focused CI/CD.nStrong communication, collaboration, and problem-solving skills.nAbility to thrive in a fast-paced, interdisciplinary research environment.nMSc or PhD in Computer Science, ML, AI, or related field, or equivalent practical experience.nPreferred Qualifications :nExperience in scientific research environments, particularly in drug discovery, bioinformatics, cheminformatics, or computational biology.nFamiliarity with large-scale data processing frameworks (e.g., Apache Spark, Beam).nExperience with containers (e.g., Docker, Kubernetes).nContributions to open-source ML projects.n-track record of leading impactful ML projects from conception to deployment.nExperience working with very large datasets.nCulture and values
We are guided by shared values: Thoughtful, Brave, Determined, Together, and Creating An Extraordinary Company. We are committed to equal employment opportunities and welcome applicants with diverse backgrounds. If you have a disability or need accommodation, please let us know.nHybrid working : We follow a hybrid model and would require you to be able to come into the office 3 days a week (Tuesday, Wednesday, and one other day depending on team). We are open to discussing additional needs during screening.nPrivacy : When you submit an application, your data will be processed in line with our privacy policy.nWe are not including extra roles or outdated listings in this description.nNote: This job description remains focused on responsibilities and qualifications for the role and adheres to the job posting’s content.
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Engineering Manager – Machine Learning
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Engineering Manager – Machine Learning
Posted 2 days ago
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Engineering Manager – Machine Learning
We are seeking a hands-on Engineering Manager to lead and grow a talented Machine Learning team, driving innovation and delivering real-world impact through cutting-edge AI solutions.
This role blends technical leadership with people management – perfect for someone who wants to stay close to the code while also shaping a high-performing engineering culture.
What you’ll do:
- Lead, mentor, and develop a team of Machine Learning engineers and researchers.
- Stay hands-on: contribute to code, review architecture, and guide technical design decisions.
- Collaborate with product and data teams to scope, build, and scale ML-driven features and systems.
- Drive best practices across experimentation, model training, deployment, and monitoring.
- Champion engineering excellence, ensuring reliability, performance, and security in ML systems.
About you:
- Strong software engineering background with direct experience in machine learning applications.
- Proven track record leading teams – balancing delivery with career growth and mentorship.
- Proficiency in modern ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and cloud platforms.
- Comfortable working across the full lifecycle: from research prototypes to production-scale systems.
- Excellent communication skills and a collaborative mindset.
Why apply?
This is an opportunity to lead a team at the forefront of machine learning, where your work will shape next-generation products and capabilities. You’ll have the freedom to innovate, while ensuring the team operates with excellence, impact, and scalability.
Senior Program Manager, AI & Machine Learning
Posted 1 day ago
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Key responsibilities include defining program scope, objectives, and deliverables; developing detailed project plans, resource allocation strategies, and risk mitigation frameworks; and actively managing program execution, tracking progress, and communicating key updates to senior leadership and stakeholders. You will be adept at navigating the unique challenges of AI/ML development, including data acquisition and preparation, model training and validation, ethical considerations, and scalable deployment. The ideal candidate will possess a deep understanding of AI/ML concepts, methodologies, and tools, along with a proven track record of successfully delivering large-scale technology programs. Exceptional leadership, communication, and stakeholder management skills are essential for this remote-first position. You must be a proactive problem-solver, capable of driving consensus and influencing outcomes in a distributed team environment. If you are passionate about harnessing the power of AI and ML to create transformative solutions and thrive in a flexible, remote work setting, this is an unparalleled opportunity to make a significant impact. Join us in pushing the boundaries of what's possible from your home base near Wolverhampton, West Midlands, UK .
Software Engineering Manager - Machine Learning- Systematic Quant Fund
Posted today
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Engineering Manager / Tech Lead Manager
to head a small, high-performing team focused on core ML infrastructure - distributed model training, LLM hosting/fine-tuning, and scalable deployment systems. You will own technical direction, lead 6-7 experienced engineers, and drive the integration of advanced ML capabilities into real-world, high-stakes systems. This is a hands-on leadership role within a deeply technical environment. Short interview process.
Responsibilities
Lead and mentor a team of 6-7 engineers working on ML infrastructure and systems integration
Define technical direction for distributed training, hosting/fine-tuning of LLMs, and scalable deployment
Collaborate with stakeholders to bring advanced ML capabilities into production systems
Maintain high standards for production-ready, scalable, and reliable software
Qualifications
8+ years in software engineering, including team leadership
Deep ML infra & distributed systems expertise
Strong Python; working knowledge of C++/Java
Proven ability to build and scale complex, production-grade systems
Not a fit for junior or first-time managers.
ContactnIf you think you're a good match for the role and would like further info, please contact:nAli (+ nlinkedin.com/in/alexander-wilson-050
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Manager, Data Science and Machine Learning, Audit and Assurance
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Manager, Data Science and Machine Learning, Audit and Assurance – ACCA CareersnJoin to apply for the
Manager, Data Science and Machine Learning, Audit and Assurance
role at
ACCA Careers .nConnect to your Industry: Our Audit and Assurance practice encompasses skills across regulation and finance with a deep analytics capability. We harness these to provide Assurance to those charged with governance, serving the public interest. Working in Assurance means you will have an opportunity to work alongside leading experts, as we help build and enhance trust between businesses and the public, by responding to emerging issues and protecting the public interest. Providing assurance to help businesses become more resilient, agile and better prepared for the future.nResponsibilities
Providing data analytics/data science services to deliver meaningful insights to our clients and help them to understand the risks and key drivers for their business through the use of software such as Python, R, Azure, Databricks/other ML services, SQL, Tableau and Power BI.nDevelopment and delivery of new and innovative data science and machine learning tools and solutions to support evolving audit and assurance needs.nHelping the team to support our clients in all areas of large data handling, manipulation, analysis, and modelling.nWorking effectively in diverse teams within an inclusive team culture where people are recognized for their contribution.nQualifications
Essential
Strong problem-solving skills, and capable of generating original solutions to real-world problems.nExperience of coaching junior data scientists/analysts.nExperience in reviewing code and documentation to a high standard.nExperience in using Python (pandas, numpy, scikit-learn).nEnd-to-end experience of managing multiple data science and analytics projects in different industries and with different types of data (text, numerical, categorical).nExperience in project management experience in a DevOps environment.nExperience in using cloud environment (e.g. Azure, AWS).nExperience using Git.nSolid understanding of mathematics, probability, and statistics.nDeep knowledge in a range of machine learning techniques (Supervised and unsupervised).nUnderstanding of Large Language Models, Generative AI frameworks, prompt engineering, fine tuning, resource augmentation.nStrong communication and data presentation skills with the ability to build convincing recommendations and sell these to a non-technical audience.nSelf-driven, able to work independently yet acts as a team playernAble to apply data science principles through a business lens.nDesirable
Experience of using R.nFamiliar with, preferably experienced in, Deep Learning (e.g. RNNs, CNNs) or NLP techniques (e.g. TF-IDF, word-embedding).nExperience developing Generative AI projects.nExperience of exercising software engineering best practices. E.g. test-driven development, smart data structure and algorithm selection.nExperience in using cloud environment (e.g. Azure, AWS).nExperience using Azure Databricks, Azure MLflow, Azure ML services and/or other ML services.nExperience using Excel, SQL, PowerBI, Tableau.nExperience using Docker and Kubernetes.nExperience working in an Agile development team.nExperience delivering data science for financial industry or large/complex organisations.nConnect to your business - Audit & Assurance
We know it's not just about the numbers. Often, we let the technology take care of those. It's about the creative and collective thinking of our people. We're redefining the future of audit. Come join us.nAssurance: Businesses need to be resilient and transparent in their reporting to build trust and confidence. Assurance practitioners play a key role in achieving this through independent review and challenge of management's views on a range of regulatory and reporting requirements, whether financial, operational or compliance in nature.nOther highlights
Hybrid working: You’ll be based in London with hybrid working. Our hybrid model enables collaboration in both virtual and physical spaces. Depending on role, you may work in your local office, virtual collaboration spaces, client sites, and remotely. The firm supports flexible working and wellbeing. Please check with your recruiter for specifics.nReturn to work: For this role we can offer coaching and support designed for returners to refresh knowledge and skills after a career break of two years or more.nOur commitment to you: We foster a culture where everyone belongs, feels supported and heard, with a focus on wellbeing and continuous learning. You will be supported to grow technically and personally, and to lead when ready.nSign in to set job alerts and discover more opportunities.nSeniority level
Mid-Senior levelnEmployment type
Full-timenJob function
Engineering and Information TechnologynIndustries: Accounting
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Software Engineering Manager - Machine Learning- Systematic Quant Fund | London, UK
Posted today
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Software Engineering Manager - Machine LearningnLocation:
London, UK
Top Quant fund an experienced
Engineering Manager / Tech Lead Manager
to head a small, high-performing team focused on core ML infrastructure - distributed model training, LLM hosting/fine-tuning, and scalable deployment systems.
You'll own technical direction, lead 6-7 experienced engineers, and drive the integration of advanced ML capabilities into real-world, high-stakes systems. This is a hands-on leadership role within a deeply technical environment. Short interview process.
You should have:n8+ years in software engineering, including team leadershipnDeep ML infra & distributed systems expertisenStrong Python; working knowledge of C++/JavanProven ability to build and scale complex, production-grade systems
Not a fit for junior or first-time managers.
Whilst we carefully review all applications, to all jobs, due to the high volume of applications we receive it is not possible to respond to those who have not been successful.
ContactnIf you think you're a good match for the role and would like further info, please contact:
Ali (+ nlinkedin.com/in/alexander-wilson-050
Welcome to Oxford Knight!We are dedicated International recruiters. We assist leading technologists and finance professionals into high-end roles wo.nBoost your career Find thousands of job opportunities by signing up to eFinancialCareers today.
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Machine Learning Engineer
Posted 13 days ago
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Job title: Machine Learning Engineer
Locations: Manchester or Haywards Heath (hybrid working)
Role overview
Markerstudy Group have an exciting opportunity for a machine learning engineer to fill out the automation, pipelining, DevOps, and modelling aspects of Markerstudy’s market-leading technical modelling and pricing team. You will productionise novel insurance modelling processes as an automated machine learning pipeline within a cloud-based environment.
Markerstudy is a leading provider of private insurance in the UK, insuring around 5% of the private cars on the UK roads, 20% of commercial vehicles and over 30% of motorcycles in total premium levels of circa £1b. Most of Markerstudy’s business is written as the insurance pricing provider behind household names such as Tesco, Sainsbury’s, O2, Halifax, AA, Saga and Lloyds Bank to list a few.
As a Machine Learning Engineer, you will help build and maintain the pricing team’s MLOps and ML Lifecycle environment to support the creation of pipelines by automating the sophisticated machine learning models and processes that underpin our market-leading technical modelling and pricing function.
Key Responsibilities:
- Build an MLOps / DevOps environment to support machine learning automation li>Build the pipelines that automate the regular model update and monitoring processes
- Build a framework that supports the creation, deployment, maintenance, and monitoring elements that non-data scientist and machine learning analysts produce, including assisting with hyper-parameter tuning, feature engineering, feature selection, and validation, reporting and visualisation, and communication processes.
- Work closely with the data science team to integrate modelling approaches and techniques
Key Skills and Experience:
- Previous experience as a DevOps / MLOps engineer
- Experience in Azure ML or databricks, or similar industry approved technology stack (i.e. AWS, Kubernetes and Docker, Google Cloud)
- Understanding of machine learning models and the modelling process, from data ingestion and cleaning to deployment and modelling – from the ground-up, not only through the use of packages and libraries < i>Proficient at communicating results in a concise manner both verbally and written
- Previous industry experience in a STEM role or educated to the Master’s level in a STEM or DS / ML / AI or maths-based discipline.
Behaviours:
- < i>Collaborative and team player
- Logical thinker with a professional and positive attitude
- Passion to innovate and improve processes
- Strong grasp of industry standards, and proficient in either Python, R, or both
Machine Learning Engineer
Posted 13 days ago
Job Viewed
Job Description
Job title: Machine Learning Engineer
Locations: Manchester or Haywards Heath (hybrid working)
Role overview
Markerstudy Group have an exciting opportunity for a machine learning engineer to fill out the automation, pipelining, DevOps, and modelling aspects of Markerstudy’s market-leading technical modelling and pricing team. You will productionise novel insurance modelling processes as an automated machine learning pipeline within a cloud-based environment.
Markerstudy is a leading provider of private insurance in the UK, insuring around 5% of the private cars on the UK roads, 20% of commercial vehicles and over 30% of motorcycles in total premium levels of circa £1b. Most of Markerstudy’s business is written as the insurance pricing provider behind household names such as Tesco, Sainsbury’s, O2, Halifax, AA, Saga and Lloyds Bank to list a few.
As a Machine Learning Engineer, you will help build and maintain the pricing team’s MLOps and ML Lifecycle environment to support the creation of pipelines by automating the sophisticated machine learning models and processes that underpin our market-leading technical modelling and pricing function.
Key Responsibilities:
- Build an MLOps / DevOps environment to support machine learning automation li>Build the pipelines that automate the regular model update and monitoring processes
- Build a framework that supports the creation, deployment, maintenance, and monitoring elements that non-data scientist and machine learning analysts produce, including assisting with hyper-parameter tuning, feature engineering, feature selection, and validation, reporting and visualisation, and communication processes.
- Work closely with the data science team to integrate modelling approaches and techniques
Key Skills and Experience:
- Previous experience as a DevOps / MLOps engineer
- Experience in Azure ML or databricks, or similar industry approved technology stack (i.e. AWS, Kubernetes and Docker, Google Cloud)
- Understanding of machine learning models and the modelling process, from data ingestion and cleaning to deployment and modelling – from the ground-up, not only through the use of packages and libraries < i>Proficient at communicating results in a concise manner both verbally and written
- Previous industry experience in a STEM role or educated to the Master’s level in a STEM or DS / ML / AI or maths-based discipline.
Behaviours:
- < i>Collaborative and team player
- Logical thinker with a professional and positive attitude
- Passion to innovate and improve processes
- Strong grasp of industry standards, and proficient in either Python, R, or both
Machine Learning Engineer
Posted 6 days ago
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Job Description
Are you a Junior Machine Learning Engineer eager to turn messy, complex data into real-world intelligence?
We’re looking for a curious and motivated Junior ML Engineer to join a hybrid-working team building cutting-edge data intelligence tools for the financial sector. You’ll spend part of your time collaborating in person with engineers and data scientists, and part working remotely — giving you the best of both worlds.
You’ll be working on a platform that transforms unstructured private market data into actionable insights — learning how to design ML pipelines, fine-tune NLP models, and deploy solutions that really work in production.
In this role, you’ll help train, test, and optimise models that can read, understand, and structure complex documents at scale. From data preprocessing to model evaluation, you’ll gain hands-on experience across the machine learning lifecycle — while contributing to a product used by real-world clients.
What’s in it for you?
AI That Matters – Work on models that make sense of unstructured financial documents and turn them into structured insights.
Hands-On ML Experience – Learn the full ML workflow — from cleaning data to deploying models and monitoring them in production.
Mentorship & Growth – Work closely with experienced ML engineers who will guide your technical and career development.