1 to 25 of 614 Machine Learning Jobs in the South East

on efficiency, adaptability, and security . Algorithm & Model Development Develop and optimize AI algorithms for predictive analytics, recommendation engines, and automation in professional services. Apply machine learning (ML) and deep learning (DL) techniques to enhance decision-making and business intelligence. Data Engineering & Integration Architect robust data pipelines to support AI model training and inference. Implement automated data … inputs. Collaborate with data engineering teams to align AI solutions with real-world business applications. AI Model Training, Evaluation & Performance Optimization Train AI models using supervised, unsupervised, and reinforcement learning techniques , refining them based on business insights . Define model performance metrics to ensure AI solutions deliver tangible value. Real-Time AI Applications & System Integration Work alongside software engineers … and collaboration skills in cross-functional teams . Preferred Skills High-Performance Computing (HPC) and AI workloads for large-scale enterprise solutions. NVIDIA CUDA, cuDNN, TensorRT experience for deep learning acceleration. Big Data platforms (Hadoop, Spark) for AI-driven analytics in professional services. Pls share CV at payal.c@hcltech.com More ❯

Job Description Salary- 90k-100k, plus 25k bonus Role Overview As Head of AI, you will be the primary technical driver of all AI/ML initiatives. You’ll report directly to the CEO/CTO and own the full lifecycle of our AI roadmap—from research and proof-of-concept to scalable production. We’re looking for a “doer … integrate AI features into our platform. • Continuously evaluate new research, open-source tools, and emerging frameworks to keep us at the forefront. • Recruit, mentor, and grow an AI/ML team as we scale beyond our seed round. ⸻ Key Responsibilities 1. Architecture & Hands-On Development • Define and implement end-to-end AI pipelines: data collection/cleaning, feature engineering, model … and maintenance of scalable data pipelines (ETL/ELT) and data lakes/warehouses. • Establish best practices for data labeling, versioning, and governance to ensure high data quality. • Implement ML Ops processes: CI/CD for model training, automated testing, model–drift detection, and continuous monitoring. 4. Team Building & Mentorship • Hire and mentor AI/ML engineers, data scientists, and More ❯

evaluation, performance tuning, and A/B testing methodologies Continuously monitor model behaviour post-deployment, addressing drift, feedback loops, and retraining strategies Contribute to and influence architectural decisions regarding ML systems and tooling (e.g., feature stores, orchestration frameworks, vector databases) Lead technical discussions, code reviews, and mentoring sessions for junior and mid-level data scientists Lead R&D initiatives by … all the skills, you have a passion and willingness for learning. Here’s what the teams will be looking for: 5+ years hands on experience in data science or ML role with a strong focus on building and deploying production systems Deep technical expertise in machine learning, including supervised/unsupervised learning, NLP, and/or deep … learning Experience with large language models (LLMs), transformers, and modern NLP techniques (e.g., fine-tuning, embeddings, prompt engineering) Proven track record in designing, scaling, and maintaining ML systems in production (cloud-native solutions preferred – e.g., Azure, AWS, GCP) Excellent problem-solving skills and a passion for innovation and continuous learning Strong Python programming skills to write clean, modular More ❯

continuous years, and unspent criminal record check (known as Disclosure and Barring Service) Your Role We are looking for people with strong technical knowledge in areas such as machine learning, GenAI, computer vision, and data science, combined with solid solution architecture and software engineering skills, that will allow us to design and build solutions which can be deployed … opportunity to author internal and public whitepapers and represent our client at conferences. Your Skills and Experience Capabilities in a range of AI techniques (e.g. supervised and un-supervised machine learning techniques, GenAI, deep learning, graph data analytics, statistical analysis, time series, geospatial, NLP, sentiment analysis, pattern detection, etc.). Strong communication skills - able to compellingly present … organisations, through e.g. the RFI/RFP process, as preferred bidder, documented bids and face to face presentations. Experience of data science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g. Keras, Tensorflow, PyTorch, scikit-learn) Cloud platforms – demonstrable experience of building and deploying solutions to Cloud (e.g. AWS, Azure, Google Cloud) including Cloud provisioning tools More ❯

continuous years, and unspent criminal record check (known as Disclosure and Barring Service) Your Role We are looking for people with strong technical knowledge in areas such as machine learning, GenAI, computer vision, and data science, combined with solid solution architecture and software engineering skills, that will allow us to design and build solutions which can be deployed … opportunity to author internal and public whitepapers and represent our client at conferences. Your Skills and Experience Capabilities in a range of AI techniques (e.g. supervised and un-supervised machine learning techniques, GenAI, deep learning, graph data analytics, statistical analysis, time series, geospatial, NLP, sentiment analysis, pattern detection, etc.). Strong communication skills - able to compellingly present … organisations, through e.g. the RFI/RFP process, as preferred bidder, documented bids and face to face presentations. Experience of data science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g. Keras, Tensorflow, PyTorch, scikit-learn) Cloud platforms – demonstrable experience of building and deploying solutions to Cloud (e.g. AWS, Azure, Google Cloud) including Cloud provisioning tools More ❯

advancements in generative AI, transformer architectures, and retrieval-augmented generation (RAG) techniques. Ensure the data security standards are met, in conjunction with the Information Security team Manage AI/ML projects and mentor junior team members Experience: Extensive experience in data collection, preprocessing, and integration from various sources, ensuring accuracy, consistency, and handling missing values or outliers. Proficient in designing … applications. Hands-on experience with natural language processing (NLP) techniques and developing custom solutions using large language models (LLMs) for business use cases. Proficient in Python-based AI/ML development using frameworks like TensorFlow, PyTorch, and Scikit-learn. Expertise in building LLM-powered applications using frameworks such as LangChain and LangGraph, including prompt engineering, fine-tuning, and workflow orchestration. … LangChain/Langraph: Experience building LLM-powered applications with prompt m anagement/chaining and integration with various LLM providers. BigQuery: Advanced knowledge of data warehousing/analytics, BigQuery ML for in-database machine learning, query optimization techniques. Google Cloud Storage (GCS): Experience with data lake management, storage/retrieval processes, lifecycle management. Desirable ITIL Foundation in IT More ❯

Foster a culture of innovation, collaboration, and continuous learning within the team. Emerging Technologies: Stay abreast of emerging technologies, tools, and industry trends in data platforms, AI/ML, and big data. Proactively evaluate and recommend new technologies that enhance data capabilities and drive business innovation. Cross-Functional Collaboration: Partner with IT, analytics, and business teams to identify data … environments and balance long-term strategy with short-term execution. Preferred Qualifications: Certifications in cloud platforms (AWS Certified Data Analytics, Azure Data Engineer, etc.). Experience with AI/ML technologies and data science platforms. Familiarity with DevOps, CI/CD pipelines, and Infrastructure as Code (IaC). What can you expect from Mars? Work with diverse 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. Mars is an equal opportunity employer and all More ❯

very established Data division headed up by well-regarded CDO who comes from a ‘hands on’ Data Science background. The Data Unit is filled with experienced Data Scientists, Analyst, Machine Learning Engineers, LLM specialists, and Data Engineers. We’re now actively recruiting for another Senior Data Engineer to join their team. The perfect Senior Data Engineer will love More ❯

and improvement. Implement changes to enhance efficiency, reliability, and scalability. Technical Leadership and Mentorship: Provide mentorship and leadership to the data engineering team, fostering a culture of collaboration, continuous learning, and innovation. Guide and support data engineers in their professional development and ensure adherence to best practices. Advisor Role: Serve as a trusted advisor to the Director of Data … Strong verbal and written communication skills, with the ability to convey technical information to non-technical stakeholders and collaborate effectively with diverse teams and clients. Preferred Skills: Knowledge of machine learning and AI technologies. Experience with big data tools and techniques. Familiarity with data visualization tools and reporting software. Builds open and trusting relationships Acts in the organisation 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 ❯

billion pounds of textile waste , and 10% of global carbon emissions each year. Rather than adjusting sizing after the fact, we prevent bad fit from the star t. Using machine learning and generative AI, we simulate and predict how garments will perform on real bodies, eliminating poor fit before a single item is made. It’s a shift … orchestration tools like Airbyte, AWS Step Functions, and GitHub Actions to ensure seamless deployment of dbt runs and freshness checks. Cross-Team Collaboration: Act as the bridge between product, ML, and analytics, ensuring their needs are met through scalable, transparent, and well-documented data models. Governance & Monitoring: Implement dbt tests, freshness checks, and observability practices to guarantee trust in downstream … analytics and ML applications for governance and audits. What You Bring: Experience : 5+ years in data engineering or backend development with a focus on implementing multi-tenant, data-heavy systems, ideally in a startup or fast-moving environment. Technical Stack : Languages/Tools: Python (REST API integrations), DBT, Airbyte, GitHub Actions Modern Data Warehousing: Snowflake, Redshift, Databricks, or BigQuery. Cloud More ❯

AI Engineer to join our Data and AI team . This role is ideal for someone who has a strong track record of designing, developing, and deploying AI/ML solutions in a business context—from ideation through to production. You will play a pivotal role in shaping and implementing advanced AI-driven insights and personalization strategies that optimize client … engagement and campaign performance across digital, CRM, and relationship management channels for our Financial Services client. Key Responsibilities End-to-End AI Solution Delivery: Lead AI/ML initiatives from conceptual design to production deployment, including problem scoping, data acquisition, model development, validation, deployment, and monitoring. AI-Driven Marketing Insights: Develop predictive and generative models to support audience segmentation, personalization … Monitoring: Deploy models using MLOps practices and tools (e.g., MLflow, Airflow, Docker, cloud platforms) ensuring performance, reliability, and governance compliance. Innovation & Research: Stay current on advancements in AI/ML and proactively bring forward new ideas, frameworks, and techniques that can be applied to marketing use cases. Data Strategy: Collaborate with data engineering teams to ensure the availability of clean More ❯

Spark, Kafka, or Hadoop . Proficiency in programming languages such as Python, Scala, or Java , with the ability to write efficient, scalable code . Experience working with AI/ML-driven platforms and understanding how data systems integrate with machine learning pipelines . Ability to work cross-functionally in high-performing teams, collaborating with AI researchers and engineers. More ❯

systems e.g., LLMs, RAG, Graph networks Strong experience deploying LLM’s for searching pipelines Up to date with current LLM and NLP research Experience designing, developing and deploying production machine learning pipelines Strong background in NLP techniques BS, MS or Ph.D. degree in Computer Science or related quantitative field Strong presentation skills Python for machine learning 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 ❯

the Data Engineering Manager , the Data Engineer will support and enhance the reliability of our research and analysis platform, which leverages open-source intelligence, data mining, network analysis, and machine learning to generate unparalleled insights on networks engaged in illicit financial activity. Key focus areas include system architecture, code quality, automation, and observability. To the right person, this 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 ❯

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 ❯

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 ❯

a highly skilled and experienced AI Engineer to join their growing team. In this role, you will play a crucial part in developing and deploying cutting-edge AI/ML solutions within the financial services domain. You will work closely with the Founders and team to build the world's leading AI Agents for the financial services sector. Responsibilities: ● Design … develop, and deploy high-quality AI/ML capabilities. ● Research and evaluate new AI/ML algorithms and technologies. ● Collaborate with data scientists to prepare and engineer high-quality datasets for model training and evaluation. ● Develop and maintain robust and scalable machine learning pipelines. ● Conduct rigorous model validation and performance monitoring. ● Ensure the ethical and responsible use of … AI/ML technologies. ● Stay abreast of the latest advancements in AI/ML research and industry best practices. ● Contribute to the development of best practices for AI/ML development within the organization. Qualifications: ● 7+ years of professional experience in AI/ML engineering. ● Proven experience in working with financial data and developing AI/ML solutions for financial More ❯

enabling colleagues across Rentokil Initial to get value from data To build AI models and a data science platform that enables Rentokil to derive huge value from AI, through machine learning to gen AI and beyond Key tasks: AI Data Engineering: Design, build, operate, and deploy real-time data pipelines at scale using AI techniques and best practices. … applications. Hands-on experience with natural language processing (NLP) techniques and developing custom solutions using large language models (LLMs) for business use cases. Proficient in Python-based AI/ML development using frameworks like TensorFlow, PyTorch, and Scikit-learn. LLM Orchestration and Development Expertise in building LLM-powered applications using frameworks such as LangChain and LangGraph, including prompt engineering, fine … Pipelines. Cloud Computing (Google Cloud Platform - GCP Preferred) Hands-on experience with GCP services such as Vertex AI, BigQuery, Cloud SQL, and Google Cloud Storage (GCS) for AI/ML applications. Skilled in containerization (Docker) and orchestration (Kubernetes, GKE), with a solid understanding of cloud security best practices. Benefits: Competitive salary and bonus scheme Hybrid working Rentokil Initial Reward Scheme More ❯

and modelling roadmap. Assist in acquiring vendor data and develop arguments. Provide expert mentorship for ongoing and new pricing activities. Design experiments and multivariate testing for AI evaluation. Assess machine learning solutions for feasibility and operationalize successful prototypes with Data Engineers. Use statistical techniques to optimise business performance. Develop and maintain algorithms to improve customer value and services. … ad-hoc analysis to predict, measure, and interpret business trends. Mentor data scientists and champion standard processes within the analytics community. Collaborate with DevOps and Data Engineers to deploy ML Models Set standards for R&D practices and lead meetings with partners. Refactor code into reusable libraries, APIs, and tools Help us to craft the next generation of our products … software practices (SCRUM/Agile, microservices, containerization like Docker/Kubernetes). we'd also encourage you to apply if you possess: Experience with Spark/Databricks. Experience deploying ML models via APIs (e.g., Flask, Keras). Startup experience or familiarity with geospatial and financial data. The Interview Process (subject to change): You’ll start with an introductory call with More ❯

and modelling roadmap. Assist in acquiring vendor data and develop arguments. Provide expert mentorship for ongoing and new pricing activities. Design experiments and multivariate testing for AI evaluation. Assess machine learning solutions for feasibility and operationalize successful prototypes with Data Engineers. Use statistical techniques to optimise business performance. Develop and maintain algorithms to improve customer value and services. … ad-hoc analysis to predict, measure, and interpret business trends. Mentor data scientists and champion standard processes within the analytics community. Collaborate with DevOps and Data Engineers to deploy ML Models Set standards for R&D practices and lead meetings with partners. Refactor code into reusable libraries, APIs, and tools Help us to craft the next generation of our products … software practices (SCRUM/Agile, microservices, containerization like Docker/Kubernetes). we'd also encourage you to apply if you possess: Experience with Spark/Databricks. Experience deploying ML models via APIs (e.g., Flask, Keras). Startup experience or familiarity with geospatial and financial data. The Interview Process (subject to change): You’ll start with an introductory call with More ❯