51 to 75 of 1,292 Machine Learning Jobs in the South East

15.07.2025 col-wide Job Description: Brainpool is a fast growing AI start-up, providing custom AI services for business since 2017. Brainpool network of 500 top-level AI and Machine Learning experts supporting delivery of our projects include PhD and MSc-level scientists from top universities such as UCL, Oxford, Cambridge and Harvard. Brainpool provides companies with end … and commercial people. BSc or a MSc in Mathematics, Physics, Computer Science, or an Engineering discipline (STEM). Desirable knowledge and experience Understanding of or working with AI/ML algorithms and data science. Docker and Kubernetes. Experience with Large Language Model stacks, vector databases, Haystack, open-source (Mistral, Falcon, Llama 3), and closed-source models like GPT-4 and More ❯

data community! You will work in a team of Data & AI Engineers, Data Scientists, Developers, Analysts and Architects and work on the design and build out of cutting-edge machine learning and AI services, supporting analytics and product iteration across our business. What you’ll do: Build and support esure’s data products within their industry leading platform. … processes and roll these out across our team and wider data community Work with architects on best design for data products, evaluating and experimenting with new data tools & supporting ML & AI infrastructure and workflows. Qualifications What we’d love you to bring: A passion for designing and building a robust data platform Great interpersonal skills and collaborative mindset Strong hands More ❯

data community! You will work in a team of Data & AI Engineers, Data Scientists, Developers, Analysts and Architects and work on the design and build out of cutting-edge machine learning and AI services, supporting analytics and product iteration across our business. What you’ll do: Build and support esure’s data products within their industry leading platform. … processes and roll these out across our team and wider data community Work with architects on best design for data products, evaluating and experimenting with new data tools & supporting ML & AI infrastructure and workflows. Qualifications What we’d love you to bring: A passion for designing and building a robust data platform Great interpersonal skills and collaborative mindset Strong hands More ❯

external technology vendors. Strong Story Telling skills - excellent communication, with senior management exposure. Deep understanding of business drivers/processes and ability to relate segment priorities to associated technology. Learning agility and desire to learn new technology. Strong problem analysis, negotiating and influencing skills. Proven track record to get things done in a matrixed organisation and influencing without authority. … end-to-end data platforms – covering Demand, Supply, R&D, and Commercial. Develop and deliver communication and education plans on analytics data engineering capabilities, standards, and processes. Partner with machine learning engineers, BI, and solutions architects to develop technical architectures for F&N enterprise projects and initiatives. Learn about machine learning, data science, computer vision, artificial … and talented Associates, all guided by the Five Principles. Join a purpose driven company, where we’re striving to build the world we want tomorrow, today. Best-in-class learning and development support from day one, including access to our in-house Mars University. An industry competitive salary and benefits package, including company bonus. #TBDDT Mars is an equal More ❯

Company description: At Circana, we are fueled by our passion for continuous learning and growth, we seek and share feedback freely, and we celebrate victories both big and small in an environment that is flexible and accommodating to our work and personal lives. We have a global commitment to diversity, equity, and inclusion as we believe in the undeniable … Spark and PySpark. Implement data partitioning, caching, and performance tuning techniques to enhance Spark-based workloads. Work with diverse data formats (structured and unstructured) to support advanced analytics and machine learning initiatives. Workflow Orchestration (Airflow): Design and maintain DAGs (Directed Acyclic Graphs) in Apache Airflow to automate complex data workflows. Monitor, troubleshoot, and optimize job execution and dependencies … development environments. A track record of working effectively global remote teams Desirable: Experience with data modelling and data warehousing concepts. Familiarity with data visualization tools and techniques. Knowledge of machine learning algorithms and frameworks. What we offer: As well as the technical skills, experience and attributes that are required for the role, our shared behaviours sit at the More ❯

skills. Excellent collaboration skills, including working with external vendors. Effective communication skills, with experience presenting to senior management. Understanding of business processes and how technology aligns with segment priorities. Learning agility and enthusiasm for new technologies. Negotiation and influencing skills, with a proven ability to deliver in matrix organizations. Key Responsibilities Design and maintain data architecture, strategies, and pipelines … and platforms across Demand, Supply, R&D, and Commercial areas. Communicate analytics capabilities, standards, and processes effectively. Collaborate on technical architecture development with engineers and architects. Expand knowledge in machine learning, data science, AI, and related fields. What can you expect from Mars? Work with diverse, talented teams guided by our Five Principles. Join a purpose-driven company … committed to building a better tomorrow. Access to top-tier learning and development resources, including Mars University. Competitive salary and benefits, including bonuses. Mars is an equal opportunity employer. We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or other protected characteristics. Assistance and accommodations are available More ❯

Oxford, but we have many flexible and partially remote options. About Us Based in Oxford, Plyable is an award-winning startup that specialises in using the latest AI and machine learning technology to automate the quoting, design and production of tooling and parts for composite (carbon fibre) manufacturing. The demand for composites is surging, particularly in industries such … this, but would not be a part of the role unless desired) Our Culture We are a new player in a traditional manufacturing industry and the team is constantly learning and willing to question the status-quo. We take quality code very seriously. We work in small intelligent teams. We have developer freedom, meaning we have a common goal More ❯

routines to clean, normalize, and aggregate data. Apply data processing techniques to handle complex data structures, handle missing or inconsistent data, and prepare the data for analysis, reporting, or machine learning tasks. Implement data de-identification/data masking in line with company standards. Monitor data pipelines and data systems to detect and resolve issues promptly. Develop monitoring 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 ❯

include a strong foundation in the social sciences. Technical expertise Knowledge of Python is required, knowledge of R and SQL is an advantage Experience of techniques such as NLP, machine learning, and LLMs is desirable Experience with tools such as Git and Github, Docker and cloud platforms is highly desirable Policy knowledge: Beyond data science, applicants must have More ❯

in working patterns and a company-wide culture to be proud of. Core skills were looking for to succeed in the role: A strong understanding of Microsoft Azure, (Azure ML, Azure Stream Analytics, Cognitive services, Event Hubs, Synapse, and Data Factory) Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc You … model development, with an emphasis on auditability, versioning, and data security. You'll implement automated data science model testing and validation. You'll assist in the optimisation of deployed ML model scoring code in production services. You'll assist in the design and implementation of data pipelines and engineering infrastructure to embed scaled machine learning solutions. You'll … the wider engineering community. You'll collaborate closely with data scientists, data engineers, architects, and the software development team. You'll liaise with stakeholders across the business to ensure ML is being used to improve strategic business decisions and identify new areas for improvements. You'll adhere to the Group Code of Conduct and Fitness and Propriety policies, Company Policies More ❯

criteria, monitor impact, and ensure measurable value is delivered at each stage of implementation Required Skills & Experience: Proven experience in solution architecture, with a strong focus on AI/ML or GenAI or Geo-Int implementations across complex environments Hands-on experience delivering AI/GenAI solutions in networks, telecommunications, or customer experience domains is strongly preferred Deep understanding of … Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field Certifications in cloud architecture (e.g., AWS/GCP/Azure Certified Architect), AI/ML, or TOGAF are a plus Familiarity with telco architecture, OSS/BSS systems, or geospatial analytics is an advantage More ❯

data platforms using Dataproc, Dataflow, Pub/Sub, BigQuery, Cloud Spanner, and Bigtable. Define and implement real-time and batch processing pipelines for complex use cases involving streaming analytics, ML feature engineering, and automation. Act as a trusted advisor to senior technical and business stakeholders across industries (e.g., telecom, retail, financial services). Drive data quality, governance, lineage, and security More ❯

TLS, HTTPS, OAuth2, OIDC, SAML, JWT Languages - Python/Node.js/Golang Development – REST API/Microservices Desirable Skills: Multi-Cloud Knowledge/Experience - Azure/AWS. AI/ML – Vertex AI. Engagement with major blue-chip clients/financial organisations Certification GCP Professional Certification – Associate Engineer, Data, DevOps, Developer. More ❯

architectures to building and maintaining robust data platforms across multiple cloud providers. Implementation of secure data processing environments for classified information, create automated deployment pipelines for data applications and ML models, and design comprehensive multi-cloud solutions with robust monitoring systems. Leading technical transformation initiatives, working closely with data engineering teams to support their infrastructure needs, implement DataOps practices, and More ❯

architectures to building and maintaining robust data platforms across multiple cloud providers. Implementation of secure data processing environments for classified information, create automated deployment pipelines for data applications and ML models, and design comprehensive multi-cloud solutions with robust monitoring systems. Leading technical transformation initiatives, working closely with data engineering teams to support their infrastructure needs, implement DataOps practices, and More ❯

architectures to building and maintaining robust data platforms across multiple cloud providers. Implementation of secure data processing environments for classified information, create automated deployment pipelines for data applications and ML models, and design comprehensive multi-cloud solutions with robust monitoring systems. Leading technical transformation initiatives, working closely with data engineering teams to support their infrastructure needs, implement DataOps practices, and More ❯

architectures to building and maintaining robust data platforms across multiple cloud providers. Implementation of secure data processing environments for classified information, create automated deployment pipelines for data applications and ML models, and design comprehensive multi-cloud solutions with robust monitoring systems. Leading technical transformation initiatives, working closely with data engineering teams to support their infrastructure needs, implement DataOps practices, and More ❯

architectures to building and maintaining robust data platforms across multiple cloud providers. Implementation of secure data processing environments for classified information, create automated deployment pipelines for data applications and ML models, and design comprehensive multi-cloud solutions with robust monitoring systems. Leading technical transformation initiatives, working closely with data engineering teams to support their infrastructure needs, implement DataOps practices, and More ❯

architectures to building and maintaining robust data platforms across multiple cloud providers. Implementation of secure data processing environments for classified information, create automated deployment pipelines for data applications and ML models, and design comprehensive multi-cloud solutions with robust monitoring systems. Leading technical transformation initiatives, working closely with data engineering teams to support their infrastructure needs, implement DataOps practices, and More ❯

architectures to building and maintaining robust data platforms across multiple cloud providers. Implementation of secure data processing environments for classified information, create automated deployment pipelines for data applications and ML models, and design comprehensive multi-cloud solutions with robust monitoring systems. Leading technical transformation initiatives, working closely with data engineering teams to support their infrastructure needs, implement DataOps practices, and More ❯

architectures to building and maintaining robust data platforms across multiple cloud providers. Implementation of secure data processing environments for classified information, create automated deployment pipelines for data applications and ML models, and design comprehensive multi-cloud solutions with robust monitoring systems. Leading technical transformation initiatives, working closely with data engineering teams to support their infrastructure needs, implement DataOps practices, and More ❯

architectures to building and maintaining robust data platforms across multiple cloud providers. Implementation of secure data processing environments for classified information, create automated deployment pipelines for data applications and ML models, and design comprehensive multi-cloud solutions with robust monitoring systems. Leading technical transformation initiatives, working closely with data engineering teams to support their infrastructure needs, implement DataOps practices, and More ❯

architectures to building and maintaining robust data platforms across multiple cloud providers. Implementation of secure data processing environments for classified information, create automated deployment pipelines for data applications and ML models, and design comprehensive multi-cloud solutions with robust monitoring systems. Leading technical transformation initiatives, working closely with data engineering teams to support their infrastructure needs, implement DataOps practices, and More ❯

We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. The Senior Machine Learning Engineer is responsible for developing, testing and maintaining applied data science solutions and machine learning pipelines powering scalable content personalisation applications for mobile and TV … for improvement. Provides technical guidance and mentorship to junior members of the engineering team. Participates in code reviews as necessary. What you'll bring: You are a very confident ML Engineer with cloud development experience (AWS/GCP/Azure) - this is a must. Proven ability to refactor and write performant, secure and clean code. Existing experience with either TypeScript … towards both success and failure. PhD in related subjects. Extensive machine learning research background and experiences. Academic publications in machine learning related conferences or journals. ML product development experiences for content discovery on large scale customer-facing clients/devices. Team overview: Global Product We're the Global Product. We're the team behind your favourite More ❯