1,396 Computational Linguistics jobs 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.

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.

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.

Machine Learning Engineer

We are working with a new start up company who are developing state-of-the-art medical devices to monitor health systems.

Experience Required:

• MSc or PhD in ML, Biomedical Engineering, or related field

• Strong experience with PyTorch/TensorFlow and Python

• Hands-on experience with TinyML or edge ML frameworks (TFLite, TVM, etc.)

• Skilled in model optimization for constrained devices

• Comfortable in a startup environment - proactive, collaborative, and adaptable

What you'll do:

• Build and optimize deep learning models for on-device biosignal monitoring

• Work on model compression, quantization, and other techniques for edge deployment

• Collaborate closely with the CTO and technical team to deploy models in production

• Contribute across the stack - from signal processing to product and hardware integration

• Help shape the direction of a fast-moving startup
  

We are seeking a highly skilled Machine Learning Engineer to join our team on a contract basis. You will be responsible for designing, building, and deploying machine learning models into production, working closely with data scientists, software engineers, and product teams to deliver scalable AI solutions. This is an excellent opportunity for someone who thrives in fast-paced environments and enjoys solving complex problems with real-world impact.

Key Responsibilities

• Develop, train, and optimize machine learning models for production use.
• Collaborate with data scientists to turn research prototypes into production-grade solutions.
• Build robust data pipelines and feature engineering workflows.
• Deploy ML solutions into cloud environments (AWS, GCP, or Azure).
• Implement monitoring, testing, and model performance evaluation frameworks.
• Work with engineering teams to ensure seamless integration of ML models into products.
• Contribute to improving infrastructure, tooling, and best practices for ML development and deployment.

Skills & Experience

Essential:

• Strong programming skills in Python (and frameworks such as PyTorch, TensorFlow, or Scikit-learn).
• Proven experience in developing and deploying machine learning models in production.
• Solid understanding of data structures, algorithms, and software engineering principles.
• Experience with ML pipelines and orchestration tools (e.g., Airflow, Kubeflow, MLflow).
• Proficiency in working with cloud services (AWS, GCP, or Azure).
• Strong understanding of CI/CD, containerisation (Docker), and orchestration (Kubernetes).
• Excellent problem-solving skills and ability to work independently in a fast-paced environment.

Desirable:

• Experience with NLP, computer vision, or time-series forecasting.
• Familiarity with distributed computing frameworks (Spark, Ray).
• Experience with MLOps and model governance practices.
• Previous contract experience in a similar ML engineering role.

Contract Details

• Duration: 6–12 months (extension possible)
• Location: London (Hybrid working model)
• Day Rate: Competitive, depending on experience

We are seeking a highly skilled Machine Learning Engineer to join our team on a contract basis. You will be responsible for designing, building, and deploying machine learning models into production, working closely with data scientists, software engineers, and product teams to deliver scalable AI solutions. This is an excellent opportunity for someone who thrives in fast-paced environments and enjoys solving complex problems with real-world impact.

Key Responsibilities

• Develop, train, and optimize machine learning models for production use.
• Collaborate with data scientists to turn research prototypes into production-grade solutions.
• Build robust data pipelines and feature engineering workflows.
• Deploy ML solutions into cloud environments (AWS, GCP, or Azure).
• Implement monitoring, testing, and model performance evaluation frameworks.
• Work with engineering teams to ensure seamless integration of ML models into products.
• Contribute to improving infrastructure, tooling, and best practices for ML development and deployment.

Skills & Experience

Essential:

• Strong programming skills in Python (and frameworks such as PyTorch, TensorFlow, or Scikit-learn).
• Proven experience in developing and deploying machine learning models in production.
• Solid understanding of data structures, algorithms, and software engineering principles.
• Experience with ML pipelines and orchestration tools (e.g., Airflow, Kubeflow, MLflow).
• Proficiency in working with cloud services (AWS, GCP, or Azure).
• Strong understanding of CI/CD, containerisation (Docker), and orchestration (Kubernetes).
• Excellent problem-solving skills and ability to work independently in a fast-paced environment.

Desirable:

• Experience with NLP, computer vision, or time-series forecasting.
• Familiarity with distributed computing frameworks (Spark, Ray).
• Experience with MLOps and model governance practices.
• Previous contract experience in a similar ML engineering role.

Contract Details

• Duration: 6–12 months (extension possible)
• Location: London (Hybrid working model)
• Day Rate: Competitive, depending on experience

Machine Learning Engineer

Salary: Up to £90k + Equity

Location: Fully Remote in UK

I am working with an exciting start-up in the UK, who are looking for a Machine Learning Engineer to join their growing team.

As a core early team member, you’ll design, optimize, and deploy models that make real-time insights possible, all while shaping the technical direction of a fast-moving startup.

What You’ll Own:

• Build and optimize ML models
• Turn research prototypes into production-ready systems.
• Collaborate across product, hardware, and data teams to tackle real-world challenges.
• Influence technical strategy and contribute to the startup’s growth and product roadmap.

What We’re Looking For:

• Strong Python and deep learning skills (PyTorch/TensorFlow).
• Experience with TinyML frameworks (TensorFlow Lite, TVM, ExecuTorch).
• Expertise in model optimization for constrained devices (quantization, pruning, compression).
• Ability to take ownership and thrive in a fast-paced, flexible startup environment.

This role does not offer sponsorship!

If you interested, please reach out to-

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.