151 to 175 of 1,844 Machine Learning Jobs in London

clearly to all audiences. Mentor junior team members and support capability growth. Work with engineers to productionise solutions. What we’re looking for: Strong knowledge of regression, classification, and machine learning algorithms, with experience applying them in real-world settings Passion for sports analytics, with previous working experience an advantage Proficient in Python or R, with good SQL More ❯

Delta Live Tables. Collaborate with stakeholders to define technical requirements and propose Databricks-based solutions. Drive best practices for data engineering. Help clients realise the potential of data science, machine learning, and scaled data processing within Azure/Databricks ecosystem. Mentor junior engineers and support their personal development. Take ownership for the delivery of core solution components. Support More ❯

business domains to drive EPAM's data business Requirements Bachelor's degree in Computer Science, Engineering, or related field Extensive experience with Snowflake and/or Databricks Familiarity with Machine Learning and Large Language Models (LLM) Experience in building Data Warehouses and Data Lakes Expertise in Data Quality, Data Modeling, and Analytics Experience with at least one Cloud More ❯

/CD. Experience in managing cloud services like Google Cloud and AWS. Bonus points Startup experience. Data science/analyst experience - turning big data into meaningful insights. Experience building machine learning systems with LLMs, RAGs utilising embeddings. Technology Frontend: Typescript, Next.js, Vercel Backend: Go, Postgres, Encore.dev, Google Cloud Services: GitHub, Sentry, Stytch, OpenAI Perks & Benefits (for UK-based More ❯

and visualisation Communicate insights clearly to all audiences Mentor junior team members and support capability growth Work with engineers to productionise solutions Requirements: Strong knowledge of regression, classification, and machine learning algorithms, with experience applying them in real-world settings Passion for sports analytics, with previous working experience an advantage Proficient in Python or R, with good SQL More ❯

supporting them in their day-to-day tasks. As a Sr. Machine Learning Engineer, you will need to: Develop a state of the art data science and ML runtime stack in a multi-cloud environment. Lead on software engineering and software design for ML components. Understand and use computer science fundamentals, including data structures, algorithms, computability and complexity … and computer architecture. Manage the infrastructure and pipelines needed to bring models and code into production. Demonstrate end-to-end understanding of applications (including, but not limited to, the machine learning algorithms) being created. Build algorithms based on statistical modelling procedures and maintain scalable machine learning solutions in production. Apply machine learning algorithms and … libraries. Research and implement best practices to improve the existing machine learning infrastructure. Collaborate with data engineers, application programmers, and data scientists. Desired skills: Qualification in a related field such as computer science, statistics, electrical engineering, mathematics, or physical sciences. Self-starter with excellent communication and time management skills. Strong computer programming skills, with knowledge of Python, R More ❯

and visualisation Communicate insights clearly to all audiences Mentor junior team members and support capability growth Work with engineers to productionise solutions Requirements: Strong knowledge of regression, classification, and machine learning algorithms, with experience applying them in real-world settings Passion for sports analytics, with previous working experience an advantage Proficient in Python or R, with good SQL More ❯

Machine Learning Scientist to join our Recommendations team in the UK. As part of the team, you will work alongside a Product Manager, Backend Engineers, and other ML Scientists, playing a key role in building innovative models to power Depop's search engine and ranking across the app. Responsibilities: Research, design, and deliver ML solutions to address problems … within the search & discovery space, including: Learning-to-rank models Vector search & embedding models etc. Understand requirements from various partners across the business, designing machine learning solutions to solve problems such as: How can we surface relevant results for this search? How can we show users personalized results in real time? What is the right price for … and humble team player capable of working with cross-functional teams, including technical and non-technical stakeholders. Passion for learning new skills and staying up-to-date with ML algorithms. Bonus points: Experience with Databricks and PySpark. Experience with deep learning & large language models. Experience with traditional, semantic, and hybrid search frameworks (e.g., Elasticsearch). Experience working with More ❯

Lead/Senior Machine Learning Engineer £110,000-£120,000 Bonus up to 10% Shares so as they continue to grow you benefit to Hybrid working - one day a week London (with door always open policy) Are you a innovative, decisive Machine Learning Engineer looking for your next challenge? This is your chance to join a … deployment times, increasing scalability, and improving model performance through regular updates and monitoring. You will work closely with the Data Scientists and Product team to deliver scalable, production-grade ML systems. This is a super exciting time to join the business who after a number of years of great success have hit profitability and now want to grow through strategic … and non-technical stakeholders through clear storytelling Required Skills Education: Bachelor’s or Master’s degree in Statistics, Data Science, Computer Science or related field Experience: Proven experience in ML model lifecycle management ● Core Competencies: Model lifecycle: You’ve got hands-on experience with managing the ML model lifecycle, including both online and batch processes Statistical Methodology: You have worked More ❯

Lead/Senior Machine Learning Engineer £110,000-£120,000 Bonus up to 10% Shares so as they continue to grow you benefit to Hybrid working - one day a week London (with door always open policy) Are you a innovative, decisive Machine Learning Engineer looking for your next challenge? This is your chance to join a … deployment times, increasing scalability, and improving model performance through regular updates and monitoring. You will work closely with the Data Scientists and Product team to deliver scalable, production-grade ML systems. This is a super exciting time to join the business who after a number of years of great success have hit profitability and now want to grow through strategic … and non-technical stakeholders through clear storytelling Required Skills Education: Bachelor’s or Master’s degree in Statistics, Data Science, Computer Science or related field Experience: Proven experience in ML model lifecycle management ● Core Competencies: Model lifecycle: You’ve got hands-on experience with managing the ML model lifecycle, including both online and batch processes Statistical Methodology: You have worked More ❯

etc.). Strong understanding of operations, security, compliance, and governance in cloud environments. Experience with partner-aligned architectures, cloud marketplaces, and third-party solution integration. Expertise in AI/ML, data engineering, and analytics-driven solutions. Strong API and microservices architecture knowledge. Experience implementing multi-cloud and hybrid-cloud strategies. Ability to develop proof of concepts and technical demos aligned … Demonstrated ability to lead cross-functional teams across multiple geographies. Ability to manage a backlog of customers and opportunities through a structured pre-sales process. Other things to know Learning & Development There is no one-size-fits-all career path at Thoughtworks: however you want to develop your career is entirely up to you. But we also balance autonomy More ❯

to make an impact that matters, through challenging projects which demand ambitious innovation and thought leadership. Build strong relationships with a diverse range of stakeholders. Gain access to endless learning opportunities. Work closely with the range of teams within the business to bring products to life. The Role As a ServiceNow Solution Architect & PreSales Lead you will be in … knowledge of GenAI, predictive analytics, or automation workflows in enterprise environments. Familiarity with NLP frameworks (TensorFlow, PyTorch) and LLM fine-tuning techniques. ITIL certification and/or AI/ML certifications (AWS, Google Cloud). Experience with implementing scripted web services in ServiceNow, Java, and CMDB or asset integrations in ServiceNow. Knowledge of SAML, Active Directory, or LDAP. ServiceNow developer More ❯

The Machine Learning (ML) Practice team is a highly specialized customer-facing ML team at Databricks facing an increasing demand for Large Language Model (LLM)-based solutions. We deliver professional services engagements to help our customers build, scale, and optimize ML pipelines, as well as put those pipelines into production. We work cross-functionally to shape long-term … the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in LLMs, MLOps, and ML more broadly. The impact you will have: Develop LLM solutions on customer data such as RAG architectures on enterprise knowledge repos, querying structured data with natural language, and content generation … of domains Advise data teams on various data science such as architecture, tooling, and best practices Present at conferences such as Data+AI Summit Provide technical mentorship to the larger ML SME community in Databricks Collaborate cross-functionally with the product and engineering teams to define priorities and influence the product roadmap What we look for: Experience building Generative AI applications More ❯

The Machine Learning (ML) Practice team is a highly specialized customer-facing ML team at Databricks facing an increasing demand for Large Language Model (LLM)-based solutions. We deliver professional services engagements to help our customers build, scale, and optimize ML pipelines, as well as put those pipelines into production. We work cross-functionally to shape long-term … the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in LLMs, MLOps, and ML more broadly. The impact you will have: Develop LLM solutions on customer data such as RAG architectures on enterprise knowledge repos, querying structured data with natural language, and content generation … of domains Advise data teams on various data science such as architecture, tooling, and best practices Present at conferences such as Data+AI Summit Provide technical mentorship to the larger ML SME community in Databricks Collaborate cross-functionally with the product and engineering teams to define priorities and influence the product roadmap What we look for: Experience building Generative AI applications More ❯

to grow their career alongside a rapidly expanding company. As we scale, you'll have the chance to take on increasing responsibilities and help shape the future of our ML infrastructure. We're open to hiring across experience levels (1+ years) depending on skills and fit. Key Responsibilities Data Engineering: Build robust pipelines that integrate and fuse large-scale datasets … from AIS feeds, market data, satellite imagery, and proprietary sourcesEnsure data quality, consistency, and reliability across heterogeneous data streams ML Development: Design and deploy models for pattern recognition, anomaly detection, and time-series forecastingContribute to model training, validation, and optimization processes Software Engineering: Develop production ML systems in Python on Google Cloud PlatformBuild and maintain APIs for data ingestion, model … Education: BS in Computer Science, Engineering, Mathematics, or related field with relevant coursework in machine learning/statistics, software engineering principles, and database systems Core Skills: Python, ML frameworks (TensorFlow/PyTorch/scikit-learn), SQL, distributed computing, version control Experience: 1+ years in ML engineering or data engineering Mindset: Self-motivated with a growth mindset, adaptable to More ❯

to grow their career alongside a rapidly expanding company. As we scale, you'll have the chance to take on increasing responsibilities and help shape the future of our ML infrastructure. We're open to hiring across experience levels (1+ years) depending on skills and fit. Key Responsibilities Data Engineering: Build robust pipelines that integrate and fuse large-scale datasets … from AIS feeds, market data, satellite imagery, and proprietary sourcesEnsure data quality, consistency, and reliability across heterogeneous data streams ML Development: Design and deploy models for pattern recognition, anomaly detection, and time-series forecastingContribute to model training, validation, and optimization processes Software Engineering: Develop production ML systems in Python on Google Cloud PlatformBuild and maintain APIs for data ingestion, model … Education: BS in Computer Science, Engineering, Mathematics, or related field with relevant coursework in machine learning/statistics, software engineering principles, and database systems Core Skills: Python, ML frameworks (TensorFlow/PyTorch/scikit-learn), SQL, distributed computing, version control Experience: 1+ years in ML engineering or data engineering Mindset: Self-motivated with a growth mindset, adaptable to More ❯

delivery. We take new ideas seriously, no matter where or who they come from. Role Requirements We are searching for motivated, driven and proactive individuals, who will own a ML-based project, or research block to design, train and integrate a new machine learning model. The role will involve working closely with ML, software engineering and operations teams … engineering or related roles Proven track record of deploying machine learning models to production environments Experience leading technical projects and managing timelines Experience with end-to-end ML project life-cycle from research to deployment Self starter with initiative and the ability to pick up and develop projects independently Ability to work quickly and make effective decisions Intellectually … Git) Proficiency with containerisation (Docker) Proficiency with data processing tools (Pandas, NumPy) Experience using machine learning frameworks like PyTorch or TensorFlow Familiarity with cloud platforms and their ML services Benefits: MOST IMPORTANT: Your career Mentorship from senior machine learning engineers and data scientists Access to cutting-edge tools, technologies, and computing resources Clear career progression paths More ❯

of business domains such as Commercial, Finance, Supply Chain, Product, and Regulatory. You will lead the design of a scalable, trusted, and connected data architecture that enables AI/ML, advanced analytics, digital transformation, and regulatory compliance. This is a critical leadership role in advancing the organization’s data-driven enterprise vision. Core Responsibilities of the Enterprise Architect Role: Bridge … enterprise-wide data needs. Prioritizing foundational governance work vs. immediate business-driven data initiatives. Defining abstraction levels for enterprise data models and ontologies. Recommending scalable architectures for AI/ML workloads and real-time data streaming. Skills & Experience Significant experience in enterprise architecture with a strong focus on data, information, or analytics. Proven hands-on expertise with data platforms such … tools like Collibra, Informatica Axon/EDC. Knowledge of advanced data architecture concepts (e.g., data mesh, data fabric, domain-oriented design). Familiarity with data science and AI/ML platforms and their integration into enterprise strategies. Experience working in highly regulated, global environments (e.g., FMCG, finance, life sciences). Skilled in developing architecture models, roadmaps, strategies, and principles. Knowledge More ❯

Senior Managing Consultant, AI Strategy will spearhead AI-driven consulting engagements for clients-especially card issuers and other financial services organizations. You will lead multidisciplinary teams of data scientists, ML engineers, and business strategists to develop long term strategies to build AI solutions and implement AI solutions that transform how clients approach analytics, automation, and value generation. In this role … metrics. • Scale effective AI initiatives across multiple use cases, proactively addressing technical or organizational hurdles to ensure widespread adoption. 2. Lead Rapid, Iterative AI Delivery • Partner with AI and ML engineering leaders to oversee project roadmaps, ensuring iterative versioning, pilot rollouts, and timely stakeholder updates. • Collaborate closely with business leaders to co-own solutions, gather continuous feedback, and adjust scopes More ❯

security Collaborate with business analysts, data scientists, and stakeholders across underwriting, finance, and ops Contribute to solution design, development assurance, and platform evolution Support delivery of data models, APIs, ML integrations, and reporting tools Key Skills: Hands on experience designing and delivering solutions using Azure services including Azure Data Factory, Azure Databricks, Azure Synapse, Azure Storage, Azure DevOps. Proven track More ❯

automation, analytics, and research functions, particularly in transitioning to new platforms Expertise in cloud-based solutions (e.g., AWS) and data migration projects Technical Expertise Advanced knowledge of AI/ML technologies, automation tools, and analytics platforms Strong understanding of data integration, pipelines, and cloud-based workflows Proficiency in programming languages (e.g., Python, R, SQL) and data visualisation tools Leadership Skills More ❯

also be nice if you have: Prior experience with LLMs (OpenAI’s GPT-4o, o1, and Claude models from Anthropic) or agentic systems. Prior experience with data science/ML/NLP. Any Frontend experience. Proven expertise in building highly secure, fault-tolerant APIs. Experience building high-performance, distributed systems at scale. A strong understanding of modern dev practices like More ❯

We strive to be better - We may make mistakes, but always learn from them. We are inclusive - to better reflect and serve our users. About the role The AI & ML Applications team is committed to empower other Zepz teams to leverage data in order to solve analytical problems. We are a team of data scientists and machine learning engineers that work together to go from ideation to production. We own end-to-end data engineering pipelines and ML models that span multiple applications (think fraud detection, time series prediction of financial data, churn prediction, and more). What you will do Help shape what we build. Our current tech stack includes Airflow, Fivetran, DBT, Databricks as well … maintainable code to solve problems. We understand code is read more than it's written, and better off tested. Maintainability is a must. Extensive industrial experience designing and productionising ML systems. Solid understanding of Machine Learning fundamentals and ability to translate business requirements into machine learning solutions. Experience in statistical experiment design and performance analysis of More ❯

DESCRIPTION The Generative AI Innovation Center at AWS helps AWS customers accelerate the use of Generative AI and realize transformational business opportunities. This is a cross-functional team of ML scientists, engineers, architects, and strategists working step-by-step with customers to build bespoke solutions that harness the power of generative AI. As an ML Engineer, you'll partner with … and innovate in a fast-paced organization that contributes to game-changing projects and technologies. We're looking for Engineers and Architects capable of using generative AI and other ML techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. Key job responsibilities - Collaborate with ML scientist and engineers to research, design and develop … help define product direction. About the team Generative AI Innovation Center is a program that pairs you with AWS science and strategy experts with deep experience in AI/ML and generative AI techniques to: - Imagine new applications of generative AI to address your needs. - Identify new use cases based on business value. - Integrate Generative AI into your existing applications More ❯

Senior Machine Learning Scientist (Generative AI) - Viator London, England About Viator Viator, a Tripadvisor company, is the leading marketplace for travel experiences. We believe that making memories is what travel is all about. And with 300,000+ travel experiences to explore—everything from simple tours to extreme adventures (and all the niche, interesting stuff in between)—making memories … instruction tuning. Define best practices for model monitoring, including output quality, hallucination detection, and user feedback loops. Understanding use cases for Agentic AI communicating your findings with the wider ML team and product. Utilize RLHF methodologies to build feedback mechanisms that directly shape the behavior and quality of our generative AI outputs. Collaborate cross-functionally with product, design, and engineering … data science experience with at least 2 years of experience with LLM. Awareness of current LLM techniques, prompt tuning, evaluations and model monitoring. In-depth knowledge of AI/ML/DL, Statistics, and related open-source libraries. Strong skills in SQL and at least one programming language. To be comfortable in code reviews, discussing architecture, and collaborating with a More ❯