1 to 25 of 176 Machine Learning Jobs in the City of London

A rare chance to take on a global ML leadership role in a high growth SaaS analytics company in London, where machine learning is central to product and strategy. The Opportunity This is a chance to lead the development of sophisticated machine learning systems that deliver real time, mission critical insights for clients around the world. … ll tackle some of the most complex challenges in real time analytics and forecasting, driving innovation and delivering real world impact across global markets. This isn't just any ML leadership role. You'll work with vast, complex datasets and deploy models with stringent latency requirements. You'll be empowered to build an architecture that blends innovation with operational excellence … built a deeply technical, forward thinking engineering culture where machine learning isn't just a function, it's a core capability. Actively leading the way in applied ML development, they invest heavily in modern tools, infrastructure, and talent to stay ahead of the curve. Why this role? ** Own the full machine learning lifecycle from research to More ❯

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 … 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 More ❯

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 … 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 More ❯

About the Opportunity: We are seeking an ambitious and intellectually curious Junior Data Scientist to join a fast-growing, forward-thinking team working at the forefront of data science, machine learning, and applied AI. This is an excellent opportunity for a recent Master’s graduate eager to apply their academic expertise to solving real-world challenges—whether it … s predicting customer behaviour, optimising operations, or identifying patterns in complex datasets. You’ll collaborate with experienced data scientists, machine learning engineers, and subject-matter experts to design, develop, and deploy models that deliver meaningful impact across a variety of industries. What You’ll Be Doing: Designing and building machine learning models to solve real-world … B testing Presenting findings clearly to both technical and non-technical stakeholders Collaborating across data science, engineering, and product teams to build scalable solutions Staying current with advancements in machine learning and AI, and contributing new ideas to internal R&D discussions What We’re Looking For: A recently completed Master’s degree from a Russell Group university More ❯

Manage multiple projects from inception to deployment within cloud-based environments. Maintain high standards in code review, documentation, and delivery in a DevOps context. Apply a deep understanding of ML techniques, from supervised/unsupervised learning to generative AI and large language models. What We’re Looking For Essential Skills and Experience: Proven ability to solve complex, real-world … Experience managing multiple end-to-end data science projects across varied data types. Familiarity with DevOps practices and tools like Git. Cloud experience (e.g. Azure, AWS) and working with ML platforms and services. Strong communication skills, capable of explaining complex topics to non-technical stakeholders. Ability to align data science efforts with broader business objectives. Desirable Skills: Experience using R … and NLP or deep learning techniques (e.g. TF-IDF, word embeddings, CNNs, RNNs). Familiarity with Generative AI and prompt engineering. Experience with Azure Databricks, MLflow, Azure ML services, Docker, Kubernetes. Exposure to Agile development environments and software engineering best practices. Experience working in large or complex organisations or regulated industries. Strong working knowledge of Excel, SQL, Power BI More ❯

the entire delivery lifecycle—from design and development to testing, deployment, and ongoing support. You will work across the full machine learning workflow, applying advanced analytics and ML techniques to extract structured insights from complex insurance submission documents, conduct exposure analytics, and model asset behaviour for the commercial insurance market. Responsibilities Design, build, and deploy machine learning … in version control, testing, CI/CD, and MLOps Share expertise through peer code reviews, documentation, and collaborative learning initiatives Stay current with emerging trends in AI/ML, particularly in areas such as LLMs, NLP, and intelligent document automation What skills and experience will I need to bring with me? You’ll need to be able to demonstrate … all the skills, you have a passion and willingness for learning. Here’s what the teams will be looking for: 3–5 years of professional experience in data science ML, or applied AI role Strong problem-solving and analytical skills with the ability to approach complex technical challenges independently Proven experience in building, deploying, and maintaining ML models in production More ❯

the entire delivery lifecycle—from design and development to testing, deployment, and ongoing support. You will work across the full machine learning workflow, applying advanced analytics and ML techniques to extract structured insights from complex insurance submission documents, conduct exposure analytics, and model asset behaviour for the commercial insurance market. Responsibilities Design, build, and deploy machine learning … in version control, testing, CI/CD, and MLOps Share expertise through peer code reviews, documentation, and collaborative learning initiatives Stay current with emerging trends in AI/ML, particularly in areas such as LLMs, NLP, and intelligent document automation What skills and experience will I need to bring with me? You’ll need to be able to demonstrate … all the skills, you have a passion and willingness for learning. Here’s what the teams will be looking for: 3–5 years of professional experience in data science ML, or applied AI role Strong problem-solving and analytical skills with the ability to approach complex technical challenges independently Proven experience in building, deploying, and maintaining ML models in production More ❯

Back End Engineer - Java, Python, AWS, MySQL, NoSql, REST APIs, Microservices, Machine Learning, Artificial intelligence (Remote or Hybrid - You choose!) Back End Engineer:- You will be joining a fast-growing, research-driven company building an artificial intelligence using novel machine learning techniques. My client is revolutionising their industry with a track record of building things that … knowledge of Cloud Technologies (AWS) and Microservices Degree in Computer Science, Engineering, or a related field, or equivalent hands-on experience in engineering. Experience or interest in AI or Machine Learning Salary for the Back End Engineer (Java) will depend on experience, but expect between £50,000 and £70,000 + Pension + benefits Other benefits include:- Free … games etc.) The latest tech, generous annual leave and an amazing office with a balcony overlooking Notting Hill. Back End Engineer - Java, Python, AWS, MySQL, NoSql, REST APIs, Microservices, Machine Learning, Artificial intelligence (Remote or Hybrid - You choose!) Applicants must have the right to work in the UK, no sponsorship is offered for this role More ❯

a top-tier quantitative firm. International Talent: Yes, international applicants are encouraged. These roles are for a professional with a global perspective, ready to apply their sophisticated expertise in machine learning to London’s prestigious financial markets. Are you interested in joining environments where your research will directly influence strategies with a substantial AUM? Individuals who are seeking … the future of quantitative and discretionary trading should take this opportunity seriously. 🔷 The Profile – Your Expertise We’re looking for professionals with a global perspective, skilled in applying advanced machine learning techniques to financial data. They have a demonstrable history of developing and deploying sophisticated models in institutional settings, with deep expertise in risk … management and the ability to integrate cutting-edge research into scalable, robust trading platforms that meet the highest standards of institutional finance. Career Path: Career trajectories focused on applying ML to solve complex problems in global, institutional trading environments. Histories of delivering high-impact projects that directly influence multi-million-dollar portfolios. Projects And Performance: Experience developing models for global More ❯

challenges in large language models (LLMs) and machine learning security. Following a successful Series A funding round, they’re expanding their team and looking for a talented ML Scientist to help shape the future of intelligent, secure systems. You’ll be part of a strong research group located near King’s Cross, working in a hybrid environment alongside … accomplished ML scientists with publications at top-tier conferences. Experience Required MSc or PhD in Computer Science, Machine Learning, or a related discipline Strong hands-on experience with transformer-based models/LLMs Proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow) Proven publication record at leading conferences such as NeurIPS, ICML, or ICLR On Offer … Collaborate with an elite, research-driven team in a rapidly growing sector Work on real-world applications of cutting-edge ML techniques Competitive compensation and flexible hybrid working model If you’re passionate about advancing ML research and applying it to the fast-evolving world of cybersecurity, we’d love to hear from you. Apply today More ❯

Senior Data Scientist Ai ML Python MML Japanese & English Speaking Working Pattern: Hybrid (12 days per week in office) Location: London The Data Science function plays a pivotal role in delivering advanced Artificial Intelligence capabilities across the organisation. This position focuses on designing, developing, and deploying production-grade machine learning solutions while contributing to the strategic growth of … team and collaborate closely with Software Engineers, Product Managers, and other stakeholders. The role requires strong mathematical and statistical foundations, excellent software engineering skills, and proven expertise in modern machine learning techniques, including Computer Vision, Natural Language Processing … and Deep Learning. ---------------------------------------- Key Responsibilities Design, build, and deploy advanced machine learning models and algorithms into production. Lead technical development within cross-functional teams, providing guidance on ML solution design and implementation. Translate business problems into clearly defined data science solutions and deliver end-to-end ML pipelines. Support proof-of-value initiatives and contribute to product roadmap More ❯

be themselves. Position Overview: You will join the Entrust Applied Science team as a research intern. The team consists of 20+ Applied Scientists located in London, UK. We develop machine learning and computer vision models for the Onfido product lines, in particular fraud detection and data extraction on government IDs and biometrics data. You will work together with … a team of scientist who will coach and train you during your internship. We use state-of-the-art technology (deep learning, VLMs), own a large proprietary dataset of images and videos and use a multi-GPU cluster. We use standard frameworks (python, pytorch, tensorflow, dask, AWS). We impact production directly but also the machine learning … and train models on state-of-the-art GPUs Your work will impact products used by dozens of millions of users worldwide You will be mentored by a senior machine learning scientist to make sure you are successful in your mission You will have the opportunity to publish and open-source your work You will be part of More ❯

be themselves. Position Overview: You will join the Entrust Applied Science team as a research intern. The team consists of 20+ Applied Scientists located in London, UK. We develop machine learning and computer vision models for the Onfido product lines, in particular fraud detection and data extraction on government IDs and biometrics data. You will work together with … a team of scientist who will coach and train you during your internship. We use state-of-the-art technology (deep learning, VLMs), own a large proprietary dataset of images and videos and use a multi-GPU cluster. We use standard frameworks (python, pytorch, tensorflow, dask, AWS). We impact production directly but also the machine learning … and train models on state-of-the-art GPUs Your work will impact products used by dozens of millions of users worldwide You will be mentored by a senior machine learning scientist to make sure you are successful in your mission You will have the opportunity to publish and open-source your work You will be part of More ❯

based platform. As Head of Data & Analytics, you'll shape and execute the enterprise data strategy, from building scalable pipelines and data lakes, to unlocking predictive analytics, AI, and machine learning for commercial advantage. You'll lead a talented team and ensure data becomes a true driver of growth, efficiency, and customer experience across the group. Benefits You … and optimisation of Azure Synapse, Databricks, and Power BI. Drive integration of ERP, CRM, IoT, and external datasets into a single source of truth. Deliver predictive modelling, AI, and machine learning to create measurable business value. Champion intuitive self-service analytics for business users. Implement best practice governance, ensuring compliance with GDPR, ISO 27001, and NIS2. Keep ahead … BI, with strong SQL, Python, Spark, and data modelling skills. Deep knowledge of cloud-native data architecture, data lakes, and streaming pipelines. Strong grasp of predictive analytics, AI, and machine learning applications. Excellent stakeholder management and ability to align data initiatives with business growth. Inspirational leader who can champion a data-driven culture across a complex organisation. Apply More ❯

Profitable FinTech Scale-Up Hybrid (London) or remote within the UK Up to £160,000 per annum plus stock options Python | Django | FastAPI | AWS | Rust | Postgres | Event-Driven Architecture | Machine Learning Principal Engineer - We're working with a leading fintech scale-up that's transforming how small businesses access finance. Backed by a strong track record and an … collaborative leader who has mentored teams and influenced product direction. Experience working with complex domain models and evolving codebases. Bonus skills include : Python, Django, PostgreSQL, event-driven data systems, machine learning familiarity and Front End awareness. If you're a Principal Engineer looking to combine hands-on technical leadership with real strategic influence in a product-led fintech … Profitable FinTech Scale-Up Hybrid (London) or remote within the UK Up to £160,000 per annum plus stock options Python | Django | FastAPI | AWS | Rust | Postgres | Event-Driven Architecture | Machine Learning Burns Sheehan Ltd will consider applications based only on skills and ability and will not discriminate on any grounds. More ❯

join an ambitious and interdisciplinary team applying AI to transform drug discovery and accelerate the development of life-changing medicines. This is a chance to work on cutting-edge ML research with direct real-world impact, in a collaborative environment where innovation and creativity are encouraged. This role will off you Work at the intersection of AI and life sciences … Hybrid working (3 days per week in the London office). A collaborative, inclusive culture with opportunities for growth and leadership. What you’ll do Design and develop novel ML models and algorithms. Apply deep learning and generative modelling to complex scientific problems. Collaborate with experts across biology, chemistry, physics, and engineering. Analyse, tune, and optimise experimental results. Depending … on experience: lead projects, mentor others, and shape research strategy. What you’ll bring PhD (or equivalent experience) in ML, computer science, or a related field. Proven expertise in deep learning research and model development. Strong knowledge of mathematics (linear algebra, calculus, statistics). Experience with ML frameworks such as PyTorch, TensorFlow, or JAX. A passion for applying ML More ❯

join an ambitious and interdisciplinary team applying AI to transform drug discovery and accelerate the development of life-changing medicines. This is a chance to work on cutting-edge ML research with direct real-world impact, in a collaborative environment where innovation and creativity are encouraged. This role will off you Work at the intersection of AI and life sciences … Hybrid working (3 days per week in the London office). A collaborative, inclusive culture with opportunities for growth and leadership. What you’ll do Design and develop novel ML models and algorithms. Apply deep learning and generative modelling to complex scientific problems. Collaborate with experts across biology, chemistry, physics, and engineering. Analyse, tune, and optimise experimental results. Depending … on experience: lead projects, mentor others, and shape research strategy. What you’ll bring PhD (or equivalent experience) in ML, computer science, or a related field. Proven expertise in deep learning research and model development. Strong knowledge of mathematics (linear algebra, calculus, statistics). Experience with ML frameworks such as PyTorch, TensorFlow, or JAX. A passion for applying ML More ❯

Manager to lead personalization efforts within their CRM ecosystem. You’ll develop predictive models and recommendation systems that enhance customer engagement across global markets. THE ROLE Lead development of machine learning solutions for CRM personalization. Build and optimize recommendation engines using neural networks and deep learnings, incorporating product … embeddings and other advanced features to improve relevance and performance. Collaborate with CRM and regional marketing teams to align with campaign goals and customer segmentation strategies Own the full ML lifecycle—from model design to deployment and monitoring. Partner with engineering and data teams to ensure scalable solutions. Continuously monitor and improve model performance using data insights and feedback. REQURIED … learning, particularly in recommendation systems and deep learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining More ❯

About the Company We’re working with a next-generation private markets firm that is redefining value creation by combining deep industry expertise with data science and machine learning. This is a unique opportunity to join a company that partners directly with portfolio companies to drive measurable operational and financial performance. They’re now hiring a Lead/Principal … Data Scientist to lead machine learning projects across a wide variety of real-world domains. Working closely with a multidisciplinary team, you’ll have the autonomy to shape technical approaches while staying closely tied to commercial outcomes. This role is ideal for someone who enjoys solving complex, ambiguous business problems using data science, and wants to work at … problems into measurable data science solutions that deliver commercial value Lead the design, development, and deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals to ensure scalable, production-grade solutions Act as a technical lead within project teams More ❯

You’ll collaborate with cross-functional teams to design, build, and implement data science solutions that directly feed into core product offerings. This is an exciting opportunity to apply ML and statistical techniques to real-world problems, while also developing in areas such as software engineering, data pipelines, and ethical product delivery. Key Responsibilities Collaborate with product teams to identify … opportunities for ML and data science integration Build and maintain data pipelines to support experimentation and model development Develop and deploy machine learning models in production environments Present insights and results to technical and non-technical stakeholders Apply statistical methods and model validation techniques to reach accurate conclusions Work with data engineers to ensure clean, usable datasets Contribute … research new methods, and continually build your technical capability What We’re Looking For Proficiency in Python or similar languages for scripting and model building Hands-on experience with machine learning, model deployment, and performance evaluation Strong communication skills – able to simplify complex ideas for various audiences Awareness of Agile methodologies and collaborative software development practices A self More ❯

You’ll collaborate with cross-functional teams to design, build, and implement data science solutions that directly feed into core product offerings. This is an exciting opportunity to apply ML and statistical techniques to real-world problems, while also developing in areas such as software engineering, data pipelines, and ethical product delivery. Key Responsibilities Collaborate with product teams to identify … opportunities for ML and data science integration Build and maintain data pipelines to support experimentation and model development Develop and deploy machine learning models in production environments Present insights and results to technical and non-technical stakeholders Apply statistical methods and model validation techniques to reach accurate conclusions Work with data engineers to ensure clean, usable datasets Contribute … research new methods, and continually build your technical capability What We’re Looking For Proficiency in Python or similar languages for scripting and model building Hands-on experience with machine learning, model deployment, and performance evaluation Strong communication skills – able to simplify complex ideas for various audiences Awareness of Agile methodologies and collaborative software development practices A self More ❯

partners directly with portfolio companies to drive measurable operational and financial performance—powered by data. They’re now hiring a Lead Data Scientist to lead high-impact analytics and machine learning projects across a wide variety of real-world domains. Working closely with a multidisciplinary team, you’ll have the autonomy to shape technical approaches while staying closely … problems into measurable data science solutions that deliver commercial value Lead the design, development, and deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals to ensure scalable, production-grade solutions Conduct rigorous A/B testing and performance … design choices Communicate findings and strategic insights to both technical and non-technical stakeholders About You You’re an experienced data scientist with a proven track record of using machine learning to solve real-world business challenges. You’re just as comfortable in Python as you are in a boardroom, and you’re motivated by measurable impact, not More ❯

partners directly with portfolio companies to drive measurable operational and financial performance—powered by data. They’re now hiring a Lead Data Scientist to lead high-impact analytics and machine learning projects across a wide variety of real-world domains. Working closely with a multidisciplinary team, you’ll have the autonomy to shape technical approaches while staying closely … problems into measurable data science solutions that deliver commercial value Lead the design, development, and deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals to ensure scalable, production-grade solutions Conduct rigorous A/B testing and performance … design choices Communicate findings and strategic insights to both technical and non-technical stakeholders About You You’re an experienced data scientist with a proven track record of using machine learning to solve real-world business challenges. You’re just as comfortable in Python as you are in a boardroom, and you’re motivated by measurable impact, not More ❯

a strong foundation in data science who is looking to make a meaningful impact in a high-performance, fast-paced environment. Key responsibilities Design, build, and maintain statistical or machine learning models to support sports forecasting and pricing across various markets. Extract actionable insights from large-scale sports datasets using sound mathematical and statistical principles. Translate modelling requirements … Experience working with Python or R in a production or research setting. Strong experience using data wrangling tools (e.g. Pandas, NumPy, dplyr). Solid grasp of statistical modelling and machine learning, with hands-on use of libraries such as scikit-learn, xgboost, PyMC3, TensorFlow. Experience working with SQL and relational databases. Ability to explain model behaviour through visualisations … contribute to cross-functional discussions. Proven problem-solving and time management skills. Desirable: Familiarity with cloud services (e.g. AWS S3, Athena, Lambda). Basic understanding of data engineering or ML pipelines. Knowledge of distributed systems (e.g. Kafka). Interest in American sports or the betting industry. Some exposure to .NET-based systems or application integration. Follow our company page, OTA More ❯

on streamlining and improving performance by reimagining value creation capabilities. They are utilising cutting-edge AI to generate performance insights on each aspect of the investment lifecycle. Responsibilities: Build machine learning predictive models to anticipate/avoid asset downtime … and reducing customer churn Evaluate and optimise all models, identifying areas for development Work end-to-end both building and deploying models Stay updated with the latest developments in ML/AI, and related fields to keep the company at the forefront of technological advancements Stay updated on emerging technologies, trends, to recommend and implement innovative solutions that drive business … effectively in a fast-paced, collaborative environment. How to Apply: Please register your interest by sending your CV to Emily Burgess via the Apply link on this page. Keywords: Machine Learning, Data Science, start-up, Investment, Equity More ❯