What Jobs are available for Machine Learning in the United Kingdom?

Job Title: Machine Learning Engineer

Location: London, UK (Hybrid – 2–3 days onsite per week)

Contract Type: Contract

Duration: 6–12 months (possibility of extension)

Start Date: ASAP

Overview

We are seeking an experienced Machine Learning Engineer to join our data science and AI engineering team on a contract basis in London. The ideal candidate will be responsible for designing, developing, and deploying machine learning models and scalable data pipelines that support advanced analytics and intelligent automation initiatives.

This role offers a hybrid work arrangement , combining flexibility with collaboration, and is ideal for a contractor who thrives in fast-paced, data-driven environments.

Key Responsibilities

• Design, build, and deploy machine learning models and AI-driven solutions to address business challenges.
• Collaborate with data scientists to transition prototypes into production-ready systems .
• Develop and maintain end-to-end ML pipelines for data ingestion, training, testing, and deployment.
• Optimise model performance, scalability, and reliability using MLOps best practices.
• Work with large-scale structured and unstructured datasets for model training and validation.
• Implement model monitoring, versioning, and retraining processes to ensure continuous improvement.
• Collaborate cross-functionally with engineering, data, and product teams to integrate ML solutions into production environments.
• Stay current with emerging trends in AI/ML technologies and contribute to innovation within the organisation.

Required Skills & Experience

• Proven experience (3–5+ years) as a Machine Learning Engineer , Data Scientist , or similar role.
• Strong programming skills in Python (experience with libraries such as TensorFlow, PyTorch, scikit-learn, pandas, NumPy).
• Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures .
• Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI).
• Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms.
• Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration.
• Knowledge of containerization and orchestration tools (Docker, Kubernetes).
• Experience integrating ML models into production environments via APIs or microservices.
• Excellent problem-solving, analytical, and communication skills.

Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science , Data Science , Mathematics , or a related field.
• Familiarity with CI/CD pipelines for ML model deployment.
• Exposure to natural language processing (NLP) , computer vision , or reinforcement learning projects.
• Experience working in Agile/Scrum environments.

Contract Details

• Location: Hybrid – London (onsite 2–3 days per week)
• Type: Day-rate contract (Outside/Inside IR35 subject to assessment)
• Duration: 6–12 months (extension likely)
• Start Date: Immediate or within 2–4 weeks

Why Join

• Work with a talented, cross-functional AI and data engineering team.
• Contribute to cutting-edge ML solutions in a collaborative, innovation-driven environment.
• Hybrid flexibility with a strong London presence.

A leading global hedge fund is looking to speak with Machine Learning researchers from any industry background who might be interested in applying their expertise to the trading domain. You'll be working alongside experienced portfolio management/trading teams to research and implement machine learning strategies to search for alphas in large, unstructured data sets.

Requirements:

-PhD in Machine Learning or related discipline.

-3+ years industry experience applying innovative ML research to real-world problems.

-Experience with large-scale data sets and unstructured data sources.

-Interest in quantitative trading.

-Hands-on coding experience in Python and/or compiled languages.

Job Title: Machine Learning Engineer

Location: London, UK (Hybrid – 2–3 days onsite per week)

Contract Type: Contract

Duration: 6–12 months (possibility of extension)

Start Date: ASAP

Overview

We are seeking an experienced Machine Learning Engineer to join our data science and AI engineering team on a contract basis in London. The ideal candidate will be responsible for designing, developing, and deploying machine learning models and scalable data pipelines that support advanced analytics and intelligent automation initiatives.

This role offers a hybrid work arrangement , combining flexibility with collaboration, and is ideal for a contractor who thrives in fast-paced, data-driven environments.

Key Responsibilities

• Design, build, and deploy machine learning models and AI-driven solutions to address business challenges.
• Collaborate with data scientists to transition prototypes into production-ready systems .
• Develop and maintain end-to-end ML pipelines for data ingestion, training, testing, and deployment.
• Optimise model performance, scalability, and reliability using MLOps best practices.
• Work with large-scale structured and unstructured datasets for model training and validation.
• Implement model monitoring, versioning, and retraining processes to ensure continuous improvement.
• Collaborate cross-functionally with engineering, data, and product teams to integrate ML solutions into production environments.
• Stay current with emerging trends in AI/ML technologies and contribute to innovation within the organisation.

Required Skills & Experience

• Proven experience (3–5+ years) as a Machine Learning Engineer , Data Scientist , or similar role.
• Strong programming skills in Python (experience with libraries such as TensorFlow, PyTorch, scikit-learn, pandas, NumPy).
• Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures .
• Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI).
• Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms.
• Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration.
• Knowledge of containerization and orchestration tools (Docker, Kubernetes).
• Experience integrating ML models into production environments via APIs or microservices.
• Excellent problem-solving, analytical, and communication skills.

Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science , Data Science , Mathematics , or a related field.
• Familiarity with CI/CD pipelines for ML model deployment.
• Exposure to natural language processing (NLP) , computer vision , or reinforcement learning projects.
• Experience working in Agile/Scrum environments.

Contract Details

• Location: Hybrid – London (onsite 2–3 days per week)
• Type: Day-rate contract (Outside/Inside IR35 subject to assessment)
• Duration: 6–12 months (extension likely)
• Start Date: Immediate or within 2–4 weeks

Why Join

• Work with a talented, cross-functional AI and data engineering team.
• Contribute to cutting-edge ML solutions in a collaborative, innovation-driven environment.
• Hybrid flexibility with a strong London presence.

We are looking for a

Machine Learning Engineer

Location: London

Reporting to: Head of AI

The role

We are looking for a talented Machine Learning Engineer who thrives in environments where reliability, scale, and impact truly matter.

At Rightmove, you'll join a close-knit, collaborative AI team that's developing, shipping and operating live ML/AI services that help Rightmove deliver exceptional experiences and value to consumers, our partners and all our stakeholders across the UK property market.

You'll be at the heart of a greenfield opportunity - building, deploying, and operating machine learning systems that leverage Rightmove's data at large scale. You'll have the opportunity to shape best practices, own and grow the ML Ops discipline, and help us move from first launches to robust, sustainable production.

In this role, you will work in a cross-functional team to productionise machine learning and AI models, ensuring they are robust, scalable, and measurable. You'll collaborate closely with data scientists, engineers, and product teams to automate workflows, monitor performance, and retrain models as needed.

You'll bring a passion for building reliable ML infrastructure, a strong technical foundation in modern machine learning engineering, and a track record of working in environments where reliability and scale are paramount.

Our Data & Analytics team has grown significantly over the last 18 months, with strong ongoing investment in infrastructure, tooling, and talent. This is a unique opportunity to own high-impact projects, help define our AI roadmap, and influence the future of how the UK engages with property.

A typical week as a Machine Learning Engineer might involve;

• Designing, building, and maintaining ML pipelines for training, deployment, monitoring, and retraining at scale.
• Working with data scientists to take models from development to production-grade systems, ensuring scalability, reproducibility, and robustness.
• Automating feature engineering and data pipeline processes, ensuring reproducibility and auditability.
• Implementing monitoring and observability to detect drift, bias, and performance degradation, and setting up rollback/recovery processes.
• Using MLOps tools (e.g., Vertex Pipelines, Kubeflow, Weights & Biases) for experiment tracking, model registry, and automated deployment.
• Leveraging Docker/Kubernetes and workflow orchestration tools (Airflow, Prefect, Dagster).
• Collaborating with product, design, and engineering teams to deliver ML features that directly impact customer experience.
• Translating model performance into business metrics (e.g., accuracy vs cost/latency trade-offs).
• Monitoring deployed solutions in production and automating retraining as needed.
  Sharing knowledge across the data and AI community at Rightmove.

We're looking for someone who;

• Has impactful experience deploying and maintaining ML systems in production, ideally in larger, mature organizations or teams operating at significant scale (e.g., web-scale, distributed systems, cloud-native environments).
• Brings expertise in MLOps: CI/CD pipelines, Docker, Kubernetes, workflow orchestration (Airflow, Prefect), and automation.
• Has experience across and understands the full ML lifecycle. Can design for long-term scalability, reliability, and resilience.
• Has strong programming skills with Python – essential. Has hands-on experience with ML frameworks (PyTorch, TensorFlow, Scikit-learn).
• Is experienced with cloud platforms (ideally GCP: BigQuery, Vertex AI, Dataflow), but AWS/SageMaker or similar is also valued.
• Has operated in distributed computing environments, working with large datasets and parallelized processing.
• Can communicate technical concepts and trade-offs to both technical and non-technical audiences.
• Is proactive, detail-oriented, and motivated to learn emerging ML engineering tools.
• Has experience working within cross-functional teams and collaborating across teams.
  Keeps abreast of the latest advancements in machine learning engineering, MLOps, and generative AI.

We would love someone to have any of the following

• Bachelor's, Master's, or PhD in Computer Science, Engineering, Data Science, or a related STEM subject (with a focus on software development or distributed systems).
• 3+ years of experience as an ML Engineer, MLOps Engineer, Data Engineer, or similar, in a larger-scale, production-focused environment.
• Hands-on with model monitoring, observability, and retraining pipelines.
• Exposure to feature stores, registries, and experimentation frameworks.
• Familiarity with business-driven metrics and experience balancing ML performance with commercial goals.
  Experience with generative AI and LLM frameworks for fine tuning, evaluation, deployment and serving desirable.

About Rightmove

Our vision is to give everyone the belief they can make their move. We aim to make moving simpler, by giving everyone the best place to turn to and return to for access to the tools, expertise, trust and belief to make it happen.

We're home to the UK's largest choice of properties, and are the go-to destination for millions of people planning their next move, reading the latest industry news, or just browsing what's on the market.

Despite this growth, we've remained a friendly, supportive place to work, with employee #1 still working here We've done this by placing the Rightmove Hows at the heart of everything we do. These are the essential values that reflect our culture, and include:

• We create value …by delivering results and building trust with partners and consumers.

• We think bigger …by acting with curiosity and setting bold aspirations.

• We care deeply …by being real, having fun, and valuing diversity.

• We move together …by being one team - internally collaborative, externally competitive.

• We make a difference …by focusing on delivering measurable impact.

We believe in careers that open doors, and help our team develop by providing an open and inclusive work environment, offering ongoing training opportunities, and supporting charity fundraising events. And with 88% of Rightmovers saying we're a great place to work, we're clearly doing something right

If all this has caught your eye, you may well be a Rightmover in the making.

What we offer

People are the foundation of Rightmove - We'll help you build a career on it.

• Cash plan for dental, optical and physio treatments
• Private Medical Insurance, Pension and Life Insurance, Employee Assistance Plan
• 27 days holiday plus two (paid) volunteering days a year to give back, and holiday buy schemes
• Hybrid working pattern with 2 days in office
• Contributory stakeholder pension
• Life assurance at 4x your basic salary to a spouse, family member or other nominated person in your life
• Competitive compensation package
• Paid leave for maternity, paternity, adoption & fertility
• Travel Loans, Bike to Work scheme, Rental Deposit Loan
• Charitable contributions through Payroll Giving and donation matching
  Access deals and discounts on things like travel, electronics, fashion, gym memberships, cinema discounts and more

As an Equal Opportunity Employer, Rightmove will never discriminate on the basis of age, disability, sex, race, religion or belief, gender reassignment, marriage/civil partnership, pregnancy/maternity, or sexual orientation.

At Rightmove, we believe that a diverse and inclusive workforce leads to better innovation, productivity, and overall success. We are committed to creating a welcoming and inclusive environment for all employees, regardless of their background or identity, to develop and promote a diverse culture that reflects the communities we serve.

Ultimately, we care much more about the person you are, and how you think and approach things, than a list of qualifications and buzzwords on a CV. Even if you can't say 'yes' to all the above, but are smart, self-motivated and passionate about Customer Care, then get in touch.

MLOps Data Engineer - Contract - Outside IR35

• Remote based
• 6 months rolling (long term contract)
• Outside IR35 contract

MLOps Data Engineer role overview:

You will be designing, building and maintaining data pipelines and machine learning infrastructure that support scalable, reliable, and production-ready AI/ML solutions. You will work closely with data scientists, engineers, and product teams to operationalize models, streamline workflows, and ensure data quality and availability.

• Develop and maintain
  data pipelines
  to support machine learning and analytics use cases.
• Implement
  MLOps best practices
  for model deployment, monitoring, and lifecycle management.
• Build and optimize
  ETL/ELT processes
  for structured and unstructured data.
• Automate workflows for
  training, testing, and deploying ML models
  .
• Ensure data
  integrity, governance, and security
  across the ML lifecycle.

MLOps Data Engineer Experience

• Strong programming skills in
  Python, SQL
  , and experience with
  AWS
• Proficiency with
  data engineering tools
  (e.g., Spark, Kafka, Airflow, dbt).
• Hands-on experience with
  MLOps frameworks
  (e.g., MLflow, Kubeflow, Vertex AI, SageMaker).
• Familiarity with
  CI/CD pipelines, containerization
  (Docker, Kubernetes)
• Solid understanding of
  data modeling, warehousing, and APIs
  .
• Strong problem-solving skills and ability to work in agile environments.

Location
: Hybrid / London or Peterborough

Team
: Data & AI

Why this role matters
At Compare the Market, we're applying AI to real-world problems that help millions of people make smarter financial decisions. As a Machine Learning Engineer, you'll work at the heart of this transformation—building the infrastructure and tooling that enables our data scientists to move from prototype to production quickly, safely, and at scale.

You'll be part of a growing ML Engineering team, contributing to a modern MLOps platform and delivering robust ML services in collaboration with product, engineering, and data science colleagues. This is a hands-on role that's ideal for someone who wants to grow in a high-impact environment with strong mentorship and real ownership.

What You'll Be Doing
ML Engineering & Deployment

• Develop and maintain machine learning pipelines for training, validation, and deployment
• Collaborate with data scientists to productionise models and turn prototypes into performant, reliable services
• Contribute to deployment tooling and automation for both batch and real-time ML use cases
• Build monitoring and alerting for model health, performance, and data drift

Platform & Standards

• Support the evolution of our internal ML platform and development workflows
• Apply best practices in testing, CI/CD, version control, and infrastructure-as-code
• Contribute to team libraries, reusable components, and shared deployment patterns

Collaboration & Growth

• Work in cross-functional teams alongside product managers, engineers, and analysts
• Participate in design sessions, peer reviews, and sprint planning
• Learn from and be mentored by experienced ML Engineers and technical leaders

What We're Looking For
Must Have

• Practical experience deploying ML models into production environments
• Strong Python development skills and understanding of ML model structures
• Familiarity with tools such as MLflow, Airflow, SageMaker, or Vertex AI
• Understanding of CI/CD concepts and basic infrastructure automation
• Ability to write well-tested, maintainable, and modular code
• Strong collaboration skills and a growth mindset
• A background in software engineering, computer science, or a quantitative field—or equivalent hands-on experience in ML delivery

Nice to Have

• Experience working in regulated sectors such as insurance, banking, or financial services
• Exposure to Databricks, container orchestration (e.g. Kubernetes), or workflow engines (e.g. Argo, Airflow)
• Familiarity with real-time model deployment, streaming data, or event-driven systems (e.g. Kafka, Flink)
• Interest in MLOps, model governance, and responsible AI practices
• Understanding of basic model evaluation, drift detection, and monitoring techniques

Why Join Us?
You'll work on meaningful problems using modern tooling, surrounded by smart, supportive people. We'll invest in your development, give you the space to grow, and the opportunity to shape how AI is delivered across Compare the Market.

Everyone Is Welcome
We're committed to building a diverse and inclusive Data & AI team where everyone feels they belong. If this role excites you but you don't meet every single requirement, we still encourage you to apply. We care about what you can do—not just where you've been.

Company Introduction
Mercor
connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include
Benchmark
,
General Catalyst
,
Peter Thiel
,
Adam D'Angelo
,
Larry Summers
, and
Jack Dorsey
.

Role Overview

• Position: Machine Learning Contractor (LLMs, RL, and Infrastructure) – Contract, Remote
• Commitment: ~35 hours/week
• Engage in research and engineering tasks focused on LLMs, RL, and infrastructure for advanced agent systems.

Responsibilities

• Build and maintain GitHub-based project infrastructure, including CI/CD workflows.
• Set up and manage environments with Docker and containerized services.
• Develop and integrate coding tool environments for agents using CLI and APIs.
• Contribute to reinforcement learning and LLM research experiments and prototypes.
• Handle data collection, preprocessing, and analytics for ML projects.
• Collaborate asynchronously with researchers and adapt to evolving project requirements.
• Document infrastructure, pipelines, and experimental results clearly and reproducibly.

Requirements / Qualifications
Must-Have Qualifications

• Background in machine learning, reinforcement learning, or related coursework.
• At least 1–2 LLM or RL-related projects (e.g., shared on GitHub).
• Proficiency with Docker, CLI tooling, and GitHub project management.
• Experience building integrations and working with data pipelines/analytics.
• Comfortable with both engineering-heavy and research-oriented tasks.

Preferred Qualifications

• Ability to navigate ambiguous requirements in fast-moving environments.
• Prior team or research lab experience is a strong plus.

Engagement Details

• Remote and flexible, with optional monthly visits to the Mercor SF office.
• Project-based, with potential for extensions based on research needs.
• Competitive hourly compensation ($35-$70 range), payments issued weekly via Stripe Connect.
• Contractors classified as independent freelancers.

Application Process (Takes 20-30 mins to complete)

• Submit your resume and links to relevant project work (e.g., GitHub repositories, Docker setups).
• Follow-up steps may include a technical assessment or project-based evaluation.
• Typical response time: within a few days of application.

Resources & Support

• For details about the interview process and platform information, please check:
• For any help or support, reach out to:

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

We are partnering with an early-stage, mission-driven company at the intersection of AI and national defence to appoint exceptional Machine Learning Engineers .

This fast-growing organisation is transforming mission-critical combat planning and operational decision-making by building next-generation AI software tools for Western forces.

Founded in 2023, the company has already secured significant early-stage funding, including a $10m Seed round in 2024. The founding team is composed of ex-Palantir and ex-OpenAI leaders. They combine deep sector knowledge with cutting-edge design and software engineering expertise to deliver state-of-the-art SaaS capabilities leveraging NLP, GenAI, Computer Vision, and Reinforcement Learning technologies.

Position location (hybrid) : London (Shoreditch) or Paris (Le Marais)

We are seeking Machine Learning Engineers who are passionate about using AI technology to solve complex, real-world problems with meaningful societal impact. You will be joining a highly collaborative and talented team that is revolutionising how operational planning is conducted at scale and speed.

Primary Responsibilities:

• Shape the company’s AI trajectory by developing AI solutions to solve high-stakes problems
• Collaborate closely with military experts, along with the product team, to identify and capitalise on high-impact opportunities
• Keep the company at the forefront of innovation by exploring and applying the latest research

Requirements:

• MSc in Machine Learning, Computer Science, or a related field
• 5+ years of experience in machine learning, with an expertise in modelling, prototyping, and evaluation
• Strong software engineering skills with a focus velocity
• Excellent communication skills and the ability to flourish in a team
• Located in London/Paris and open to working in office

Tech Stack:

• Python FastAPI
• Python, Typescript, or React
• Open source LLMs
• Building for production

Benefits Currently Offered (likely to improve as company grows):

• 100% coverage for travel expenses
• Childcare support
• Min. 3 months fully paid parental leave
• 25 days holiday + bonus days for company closure
• Subsidised lunches in office
• Gym membership
• Private medical insurance
• Subsidised coaching/training
• Work-from-home allowance to cover office equipment, desk, chair, monitor etc.
• Fertility support benefits, including financial support for IVF
• Menstrual leave/congé menstruel
• Company off-sites twice per year

Interview process:

1. Introductory interview – 45 mins
2. Live coding task – 45 mins
3. On-site interviews + meet the team – half day
4. Final interview with CEO – 30 mins

***This company is not currently offering sponsorship to foreign candidates. If you are not able to live and work in either Paris or London without sponsorship, please do not apply***

We are partnering with an early-stage, mission-driven company at the intersection of AI and national defence to appoint exceptional Machine Learning Engineers .

This fast-growing organisation is transforming mission-critical combat planning and operational decision-making by building next-generation AI software tools for Western forces.

Founded in 2023, the company has already secured significant early-stage funding, including a $10m Seed round in 2024. The founding team is composed of ex-Palantir and ex-OpenAI leaders. They combine deep sector knowledge with cutting-edge design and software engineering expertise to deliver state-of-the-art SaaS capabilities leveraging NLP, GenAI, Computer Vision, and Reinforcement Learning technologies.

Position location (hybrid) : London (Shoreditch) or Paris (Le Marais)

We are seeking Machine Learning Engineers who are passionate about using AI technology to solve complex, real-world problems with meaningful societal impact. You will be joining a highly collaborative and talented team that is revolutionising how operational planning is conducted at scale and speed.

Primary Responsibilities:

• Shape the company’s AI trajectory by developing AI solutions to solve high-stakes problems
• Collaborate closely with military experts, along with the product team, to identify and capitalise on high-impact opportunities
• Keep the company at the forefront of innovation by exploring and applying the latest research

Requirements:

• MSc in Machine Learning, Computer Science, or a related field
• 5+ years of experience in machine learning, with an expertise in modelling, prototyping, and evaluation
• Strong software engineering skills with a focus velocity
• Excellent communication skills and the ability to flourish in a team
• Located in London/Paris and open to working in office

Tech Stack:

• Python FastAPI
• Python, Typescript, or React
• Open source LLMs
• Building for production

Benefits Currently Offered (likely to improve as company grows):

• 100% coverage for travel expenses
• Childcare support
• Min. 3 months fully paid parental leave
• 25 days holiday + bonus days for company closure
• Subsidised lunches in office
• Gym membership
• Private medical insurance
• Subsidised coaching/training
• Work-from-home allowance to cover office equipment, desk, chair, monitor etc.
• Fertility support benefits, including financial support for IVF
• Menstrual leave/congé menstruel
• Company off-sites twice per year

Interview process:

1. Introductory interview – 45 mins
2. Live coding task – 45 mins
3. On-site interviews + meet the team – half day
4. Final interview with CEO – 30 mins

***This company is not currently offering sponsorship to foreign candidates. If you are not able to live and work in either Paris or London without sponsorship, please do not apply***