1,376 to 1,400 of 4,242 Machine Learning Jobs in the UK

SS1/23, Consumer Duty) Familiarity with data science processes (e.g. pipelines) and associated technologies Exposure to range of risk modelling techniques (e.g. logistic and time series regressions and Machine Learning methods, such as gradience boosting, random forests, etc.) Red Hot Rewards Generous holidays - 38.5 days annual leave (including bank holidays and prorated if part-time)plus the More ❯

transportation. What Makes Us Different: Purpose: you can use your passion and abilities at Leidos to keep the people you care about safe. We are at the forefront of machine learning, AI, cyber security and solutions. Using your skills in the technology frontline by helping to build a safer world. You can inspire change. Collaboration: having flexibility to More ❯

transportation. What Makes Us Different: Purpose: you can use your passion and abilities at Leidos to keep the people you care about safe. We are at the forefront of machine learning, AI, cyber security and solutions. Using your skills in the technology frontline by helping to build a safer world. You can inspire change. Collaboration: having flexibility to More ❯

methodologies, with the goal of reduced complexity, improved performance, and cost efficiency Collaborate with Analysts and Data Scientists to prepare and model data for predictive analytics and AI/ML initiatives Implement and maintain data observability and quality monitoring solutions, including custom alerting, to ensure the reliability and integrity of our data assets Work closely with Engineering teams to understand … days after 2 years of employment Two (paid) volunteering days a year to spend your time giving back to the causes that matter to you and your community Rich learning and development opportunities are supported through the Trustpilot Academy and Blinkist Pension and life insurance Health cash plan, online GP, 24/7, Employee Assistance Plan Full access to More ❯

ll have flexible paid time off-including national holidays, personal days, and sick days-plus stock options so you can grow with Testlio. We also provide a $300 annual learning stipend to support your personal and professional development. Winning Business : Testlio is growing, profitable, and cash-strong. We are leading our industry with exceptional clients who provide us with … microservices, and event-driven design. Experience in writing automated tests is a strong plus. Proven track record of taking ownership, conducting technical design, and successfully delivering results. AI/ML experience is a strong plus. Mobile Development: Experience in developing and optimizing mobile applications (whether using fully native frameworks for iOS/Android or cross-platform solutions such as React More ❯

analytical role in a customer-centric organisation • Familiarity with agile or other rapid application development methods • Understanding of data pipelines and/or data modelling • Experience with Data Science & Machine learning • Understanding of how digital products use experimentation and experience with A/B testing • Knowledge of R or Python About the BBC The BBC is committed to More ❯

and dashboards that provide insights and promote rapid, data-driven decisions. Collaborate with the Decision Science team to maximise value from our internal and external data through cutting-edge ML models Promote a culture of proactive, high quality analysis and ensure we have the right credit capabilities, infrastructure and talent in place to scale safely You should apply if: What … meetings in London). We offer flexible working hours and trust you to work enough hours to do your job well, at times that suit you and your team. Learning budget of £1,000 a year for books, training courses and conferences And much more, see our full list of benefits here Equal opportunities for everyone Diversity and inclusion More ❯

and dashboards that provide insights and promote rapid, data-driven decisions. Collaborate with the Decision Science team to maximise value from our internal and external data through cutting-edge ML models Promote a culture of proactive, high quality analysis and ensure we have the right credit capabilities, infrastructure and talent in place to scale safely You should apply if: What … meetings in London). We offer flexible working hours and trust you to work enough hours to do your job well, at times that suit you and your team. Learning budget of £1,000 a year for books, training courses and conferences And much more, see our full list of benefits here Equal opportunities for everyone Diversity and inclusion More ❯

experienced Machine Learning Engineer to work on incredibly interesting projects as we take our personalization capabilities to the next level. You will focus on developing and advancing ML/AI across our platforms, researching and investigating new machine learning applications within the company, and improving pre-existing models. Role & Core Responsibilities Own the model development and … and investigate new machine learning applications within the company, and improve on pre-existing models. Collaborate closely with product and development teams to define and prepare new ML applications. Analyse performance and continuously improve scoring processes for hosted models. Best Bits of the Job Exposure to a phenomenal array of machine learning domains, including massive-scale … of-the-art technologies, including Large Language Models (LLMs), to enhance our products and services. Fully real-time architecture for data processing, model development, and deployment. Deploying and enhancing ML frameworks, optimizing for inference, and training/retraining cycles. Online testing for models with live data using proprietary A/B/N testing technology to rapidly determine what works More ❯

to 1000s of accelerators. Test and evaluate new internal software releases, provide feedback to software engineering teams, make vital code fixes, and conduct code reviews. Benchmark models and key ML techniques to identify performance bottlenecks and improve model efficiency. Design and conduct experiments on novel AI methods, implement them and evaluate results. Collaborate with Research, Software, and Product teams to … Python software development skills (nice to have C other languages). Familiar with deep learning fundamentals: models, optimisation, evaluation and scaling. Capable of designing, executing and reporting from ML experiments. Ability to move quickly in a dynamic environment. Enjoy cross-functional work collaborating with other teams. Strong communicator - able to explain complex technical concepts to different audiences. Desirable: Experience … in one or more of: distributed training of large-scale ML models, building production systems with large language models, efficient computing based on low-precision arithmetic, deep learning models including large generative models for language, vision and other modalities . Experience writing C Triton/CUDA kernels for performance optimisation of ML models. Have contributed to open-source projects More ❯

to 1000s of accelerators. Test and evaluate new internal software releases, provide feedback to software engineering teams, make vital code fixes, and conduct code reviews. Benchmark models and key ML techniques to identify performance bottlenecks and improve model efficiency. Design and conduct experiments on novel AI methods, implement them and evaluate results. Collaborate with Research, Software, and Product teams to … Python software development skills (nice to have C other languages). Familiar with deep learning fundamentals: models, optimisation, evaluation and scaling. Capable of designing, executing and reporting from ML experiments. Ability to move quickly in a dynamic environment. Enjoy cross-functional work collaborating with other teams. Strong communicator - able to explain complex technical concepts to different audiences. Desirable: Experience … in one or more of: distributed training of large-scale ML models, building production systems with large language models, efficient computing based on low-precision arithmetic, deep learning models including large generative models for language, vision and other modalities . Experience writing C Triton/CUDA kernels for performance optimisation of ML models. Have contributed to open-source projects More ❯

We are looking for a Senior MLOps Engineer to join a Scottish company working on cutting edge AI solutions. You will play a pivotal role in ensuring that ML initiatives drive value effectively while maintaining operational excellence. The Role: Managing and optimising existing ML model deployments to ensure reliability and efficiency. Continuously improving the architecture, processes, and tools used for … model deployment, monitoring, and lifecycle management. Collaborating closely with data scientists to understand and implement model requirements. Partnering with R&D teams to align technical strategies and integrate ML solutions into broader systems. Implementing robust CI/CD pipelines, monitoring systems, and infrastructure automation. Upholding best practices in security, cost management, and infrastructure design for cloud environments. The Ideal Candidate … 4+ years of experience in MLOps, DevOps, or software engineering roles. Strong programming skills in Python and familiarity with ML frameworks. Extensive experience with AWS services (e.g., SageMaker, ECS, Lambda) and cloud environments. Proficiency with containerization and orchestration tools (Docker, Kubernetes). Knowledge of data engineering concepts (e.g., ETL, data pipelines). Please note we can only consider candidates who More ❯

Senior Machine Learning Engineer (UK-based, Remote/Hybrid) We're looking for a seasoned ML Engineer to take a lead role in building and integrating production-grade AI and generative AI features across a platform used by thousands. This is a hands-on engineering role where you'll design, deploy, and optimise systems that power real-world … and CI/CD Drive compute efficiency, cost-effectiveness, and sustainability Guide junior team members and improve engineering best practices 🧠 Your skillset: Expert Python dev (pandas, FastAPI, Pydantic) Strong ML/AI experience incl. AutoML, LLMs, HuggingFace, LangChain Proficiency in Linux, Git, PostgreSQL, and API development Experience deploying AI models in containerised, cloud-based environments Bonus: agentic AI (smolagents, AutoGen More ❯

data quality. Experimentation - set up offline metrics and online A/B tests; analyse uplift and iterate quickly. Production delivery - build scalable pipelines in AWS SageMaker (moving to Azure ML); containerise code and hook into CI/CD. Monitoring & tuning - track drift, response quality and spend; implement automated retraining triggers. Collaboration - work with Data Engineering, Product and Ops teams to … translate business constraints into mathematical formulations. Tech stack Python (pandas, NumPy, scikit-learn, PyTorch/TensorFlow) SQL (Redshift, Snowflake or similar) AWS SageMaker → Azure ML migration, with Docker, Git, Terraform, Airflow/ADF Optional extras: Spark, Databricks, Kubernetes. What you'll bring 3-5+ years building optimisation or recommendation systems at scale. Strong grasp of mathematical optimisation (e.g., linear …/integer programming, meta-heuristics) as well as ML. Hands-on cloud ML experience (AWS or Azure). Proven track record turning prototypes into reliable production services. Clear communication and documentation habits. Desired Skills and Experience Experience & skills checklist 3-5 + yrs optimisation/recommender work at production scale (dynamic pricing, yield, marketplace matching). Mathematical optimisation know-how More ❯

At Kortical we are on a mission to enable any company to be an AI company by providing world class tooling to enable data scientists to deliver superhuman ML solutions much quicker than than current offerings allow, all fully transparent and editable in code. Remote working: Flexible remote (up to 4 days p/w) At Kortical we are on … a mission to enable any company to be an AI company by providing world class tooling to enable data scientists to deliver superhuman ML solutions much quicker than than current offerings allow, all fully transparent and editable in code. The role has two elements to it: As not every company or department have in-house data scientists, for some clients … we build awesome ML solutions for our clients like Deloitte Tax, NHS and Santander using the Kortical platform. By working with our clients building these awesome ML solutions, we find areas that would make our life better as data scientists and encode those features into the platform, editing features and seeing the result before building a model, monitoring data drift More ❯

data quality. Experimentation - set up offline metrics and online A/B tests; analyse uplift and iterate quickly. Production delivery - build scalable pipelines in AWS SageMaker (moving to Azure ML); containerise code and hook into CI/CD. Monitoring & tuning - track drift, response quality and spend; implement automated retraining triggers. Collaboration - work with Data Engineering, Product and Ops teams to … job. Review: inspect dashboards, compare control vs. treatment, plan next experiment. Tech stack Python (pandas, NumPy, scikit-learn, PyTorch/TensorFlow) SQL (Redshift, Snowflake or similar) AWS SageMaker → Azure ML migration, with Docker, Git, Terraform, Airflow/ADF Optional extras: Spark, Databricks, Kubernetes. What you'll bring 3-5+ years building optimisation or recommendation systems at scale. Strong grasp … of mathematical optimisation (e.g., linear/integer programming, meta-heuristics) as well as ML. Hands-on cloud ML experience (AWS or Azure). Proven track record turning prototypes into reliable production services. Clear communication and documentation habits. Desired Skills and Experience Experience & skills checklist 3-5 + yrs optimisation/recommender work at production scale (dynamic pricing, yield, marketplace matching More ❯

data quality. Experimentation - set up offline metrics and online A/B tests; analyse uplift and iterate quickly. Production delivery - build scalable pipelines in AWS SageMaker (moving to Azure ML); containerise code and hook into CI/CD. Monitoring & tuning - track drift, response quality and spend; implement automated retraining triggers. Collaboration - work with Data Engineering, Product and Ops teams to … job. Review: inspect dashboards, compare control vs. treatment, plan next experiment. Tech stack Python (pandas, NumPy, scikit-learn, PyTorch/TensorFlow) SQL (Redshift, Snowflake or similar) AWS SageMaker → Azure ML migration, with Docker, Git, Terraform, Airflow/ADF Optional extras: Spark, Databricks, Kubernetes. What you'll bring 3-5+ years building optimisation or recommendation systems at scale. Strong grasp … of mathematical optimisation (e.g., linear/integer programming, meta-heuristics) as well as ML. Hands-on cloud ML experience (AWS or Azure). Proven track record turning prototypes into reliable production services. Clear communication and documentation habits. Desired Skills and Experience Experience & skills checklist 3-5 + yrs optimisation/recommender work at production scale (dynamic pricing, yield, marketplace matching More ❯

as well as the practical application of existing cutting edge techniques. Responsibilities Collaborate with cross-functional teams including Product, Engineering, and Data Engineering to translate business challenges into scalable ML solutions. Collaborate with external AI specialists to deliver larger-scale projects. Explore, clean, and transform large datasets for training, validation, and inference, including geospatial data types. Design, test, and deploy … Continuously evaluate model performance and apply strategies for tuning, retraining, or improvement. Participate in product and project planning to help prioritize AI-driven initiatives. Mentor team members by sharing ML best practices and helping to build a culture of technical excellence. Stay current with emerging ML techniques and technologies, and evaluate their potential for our use cases. Support team delivery … summarization tools, content generation workflows, or intelligent data extraction pipelines. Deep understanding of NLP fundamentals: text preprocessing, language modeling, and semantic similarity. Strong proficiency in Python, including use of ML libraries such as TensorFlow, PyTorch, or similar. Experience with data science tools and platforms (e.g., Jupyter, Pandas, NumPy, MLFlow). Familiarity with cloud-based AI tools and infrastructure, especially within More ❯

as well as the practical application of existing cutting edge techniques. Responsibilities Collaborate with cross-functional teams including Product, Engineering, and Data Engineering to translate business challenges into scalable ML solutions. Collaborate with external AI specialists to deliver larger-scale projects. Explore, clean, and transform large datasets for training, validation, and inference, including geospatial data types. Design, test, and deploy … Continuously evaluate model performance and apply strategies for tuning, retraining, or improvement. Participate in product and project planning to help prioritize AI-driven initiatives. Mentor team members by sharing ML best practices and helping to build a culture of technical excellence. Stay current with emerging ML techniques and technologies, and evaluate their potential for our use cases. Support team delivery … summarization tools, content generation workflows, or intelligent data extraction pipelines. Deep understanding of NLP fundamentals: text preprocessing, language modeling, and semantic similarity. Strong proficiency in Python, including use of ML libraries such as TensorFlow, PyTorch, or similar. Experience with data science tools and platforms (e.g., Jupyter, Pandas, NumPy, MLFlow). Familiarity with cloud-based AI tools and infrastructure, especially within More ❯

evolve our data pipeline and storage infrastructure to support faster, more reliable turnarounds for research and development of new models. You'll join a multidisciplinary team, collaborating closely with ML scientists, software developers and DevOps engineers to improve the performance and reliability of Python-based workflows. As a key contributor, you'll participate in the design, testing, and maintenance of … variety of internal and external sources into training datasets for AI models. Evolve our data storage layer to support analytics, schema evolution, reproducibility, and efficient data access. Collaborate with ML engineers to improve the performance and reliability of Python-based data processing workflows. Collaborate on the creation, testing and maintenance of software systems Code review for pull requests in adjoining … experience; or equivalent experience. Proven ability to design flexible, maintainable ETL systems. Experience with data pipeline orchestration tools such as Prefect, Airflow, Argo, Databricks, or Spark. Understanding of the ML model lifecycle; prior work with scientific or ML workflows is a plus. Hands-on experience with multi-terabyte scale data processing. Familiarity with AWS; Kubernetes experience is a bonus. Knowledge More ❯

Integrations: Implement new connections and be the master and owner of these integrations. Optimize AI Pipelines: Ensure our AI pipeline works like clockwork. Improve and support its complex infrastructure. ML Experience: Practical experience with ML, including classification, clustering, time series forecasting, and anomaly detection. You need to know the concept and be handly with the most common libraries. Model Hosting … in building and monitoring production services or APIs. Experience with third-party APIs is essential. Data Pipelining: Experience with SQL, ETL, data modeling. Experienced with the lifecycle of building ML solutions. Speak AI language: Understand the fundamentals of ML/AI and communicate effectively with AI and Data Scientists. Infra: Deep Knowledge of Docker, Git, cloud networking, and cloud security More ❯

Pavegen’s integrated systems. Lead the technical vision for connected, scalable IoT systems that combine hardware, software, data, and user experience. Stay on the pulse of emerging tech (AI, ML, Digital Twins, Edge Computing, 5G, etc.) and identify opportunities to adopt and test new technologies. Architecture & Systems Integration Architect connected systems that link our kinetic and solar hardware with backend … to platform development and UX/UI integration. Shape our data strategy: from sensor collection, cleansing, and ingestion, to analytics, visualisation, and client reporting. Explore and implement AI/ML capabilities and predictive analytics to provide deeper insights and value to customers. Leadership & Delivery Build and lead a high-performing technical team (in-house and external partners). Translate customer … JavaScript, C++, Node.js). Experience designing and managing cloud platforms (AWS, Azure, GCP), databases (SQL/NoSQL), and real-time analytics. Demonstrated experience working with or deploying AI/ML models, especially in edge or IoT contexts. Understanding of Digital Twin technologies and how they integrate with physical assets and environments. Background in building scalable, secure software systems and applying More ❯

smarter decisions faster. Now they need an exceptional Senior Data Scientist to architect the AI that powers it all. What You'll Actually Build Spatial Intelligence That Matters Design ML models that understand 3D space the way humans do (but faster, more accurately) Build predictive systems that help planners spot opportunities before anyone else Create AI that turns complex geospatial … Transform research breakthroughs into scalable solutions Key Skills Required: LLM Experience : Production experience with GPT, Claude, LLaMA, including fine-tuning, prompt engineering, and deployment Python Proficiency : Strong skills with ML frameworks (TensorFlow, PyTorch) and LLM tools (Hugging Face, LangChain, OpenAI APIs) Vector Understanding : Solid knowledge of embeddings, vector databases (Pinecone, Weaviate, FAISS), and RAG pipelines NLP Fundamentals : Text preprocessing, language … Urban planning is digitising rapidly. Position yourself as the data scientist who understands this transformation from the ground up. Their Commitment to You Intellectual Growth: Stay current with emerging ML techniques and evaluate their potential for spatial intelligence Leadership Development: Mentor team members and help build a culture of technical excellence Career Trajectory: Shape both their AI strategy and your More ❯

destinations like Home and Search as well as original playlists such as Made For You, Discover Weekly and Daily Mix. What You'll Do Design, build, evaluate, and ship ML solutions in Spotify's personalization products Collaborate with cross functional teams spanning user research, design, data science, product management, and engineering to build new product features that advance our mission … fans in personalized and useful ways Prototype new approaches and productionize solutions at scale for our hundreds of millions of active users Promote and role-model best practices of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization Be part of an active group of machine learning practitioners Who You Are … An experienced ML practitioner motivated to work on complex real-world problems in a fast-paced and collaborative environment Strong background in machine learning, natural language processing, and generative AI, with experience in applying theory to develop real-world applications Hands-on expertise with implementing end-to-end production ML systems at scale in Python, Java or Scala More ❯

conceptualisation and design to implementation, testing, and delivery of software for products and internal tools. You will collaborate closely with cross-functional teams, including Software Engineers, Data Science/ML Engineers, Systems Engineers, and the Regulatory team, to develop safe and reliable medical devices. Responsibilities: Software Development: Design and develop software for medical devices while ensuring compliance with industry standards … Background: Experience in highly regulated industries, preferably in medical device development Technical Expertise: Experience with multi-tasking systems (real-time preferable) and familiarity with signal processing or AI/ML applications using CUDA on GPUs (preferred), medical device communications protocols (HL7, FHIR) Development Approach: Knowledge of agile methodologies and best practices in software development Tools & Practices: Proficiency with version control More ❯