1 to 25 of 191 Permanent Machine Learning Jobs in Glasgow

expected salary range for this role reflects internal benchmarking and external market insights. PURPOSE OF THE ROLE As a Software Engineer within the Machine Learning Enablement Team at the BBC, you will design and deliver the tools, platforms, and capabilities that empower data scientists and engineering teams across … orchestration technologies. • Familiarity with machine learning concepts, statistical techniques, or machine learning frameworks, and experience collaborating with data scientists or ML engineers. ...

transformation in secure environments where quality, assurance and governance matter.Your work will help clients move from data science experimentation to production-ready AI and ML solutions that are scalable, explainable, secure and aligned to measurable mission outcomes.Connect to your career at Deloitte Deloitte drives progress. Using our vast range … action we take, guiding us to deliver impact how and where it matters most.Connect to your opportunity We are seeking to hire experienced ML Engineers within our AI Scaling and Transformation team, a centre of excellence in Deloitte’s Engineering, AI & Data service offering.You will work alongside clients, third parties ...

agentic workflows that tie it all together. You will partner with computational chemists, CADD scientists, software engineers, and hardware engineers, and apply AI/ML to build the next generation of Chemify's platform. What sets this role apart is the combination of breadth of ML problems — generative chemistry, vision … search, agents — paired with a robotic platform that turns your models into physical experiments. If working across a wide range of hard ML problems on a real-world platform sounds like the right shape of job for you, we'd love to welcome you to our team. Key Responsibilities Build ...

trusted delegate who can confidently represent the CTO's priorities and drive alignment at every level of the organisation. The work spans machine learning, software-defined robotics and modern agile delivery. While you won't be hands-on with model development or control software, you'll need … end. Experience in high‐growth or scale‐up environments, particularly within deep‐tech or complex engineering organisations. Familiarity with modern engineering and ML tooling and workflows, such as CI/CD pipelines, Jira or ClickUp, MLflow or Weights & Biases, and simulation or testing environments. Experience working in regulated, safety‐critical ...

take, guiding us to deliver impact how and where it matters most.Connect to your opportunity We are seeking to hire talented AI/ML Engineers within our AI Scaling and Transformation team, a centre of excellence in Deloitte’s Engineering, AI & Data service offering.You will work alongside clients, third parties … technical capability with client-facing delivery, helping to translate business needs into production-ready AI and machine learning systems.As an AI/ML Engineer, you will play a key role in designing, developing and delivering data and AI solutions for our clients. In this role ...

seeking candidates with the following knowledge & experience: An extensive background in Data Engineering with recent & relevant experience working in a similar AI Engineer/ML Engineering role Proven experience delivering AI and machine learning solutions in enterprise/large Public Sector environments First class communication skills with … technical stakeholders, clearly translating business challenges into practical AI solutions, ensuring they're fully understood Strong Python skills and hands‐on experience with ML frameworks and libraries. Experience with Generative AI, LLMs, RAG, and prompt engineering . Strong understanding of MLOps, model deployment, CI/CD, and monitoring. Experience with ...

looking for a talented Senior Algorithms Engineer to join an innovative engineering team developing advanced machine learning and computer vision solutions for complex, real-world applications. This is an exciting opportunity for an experienced engineer to work on challenging perception and intelligence problems, applying techniques across AI, computer … technically challenging projects, influence future development activities, and support the growth of engineering capability through collaboration and mentoring. Key Responsibilities Develop and optimise machine learning and computer vision algorithms for real-world applications. Investigate complex technical challenges, designing experiments and approaches to identify effective solutions. Analyse datasets, model ...

multidisciplinary teams and to manage relationships with stakeholders.Relevant industry certifications (e.g., AWS, Azure, GCP, or equivalent) and completion of technical courses in AI/ML, data engineering, or cloud technologies are desirable.TECHNICAL PROFICIENCYStrong proficiency in at least one modern programming language commonly used in AI/ML (e.g., Python … with hands-on experience developing, training, and deploying machine learning models.Practical experience with leading AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, XGBoost), including model selection, tuning, and evaluation.Experience implementing end-to-end machine learning workflows, including data preprocessing, feature engineering, model development ...

Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 – AI Prompt Engineering Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems … Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine ...

their career to new heights. Join the ranks of top talent at one of the world's most influential companies. As an Applied AI ML Lead - Vice President at JPMorgan Chase within the International Private Bank (IPB) Technology Artificial Intelligence and Machine Learning (AIML) Team, you provide deep … responsible to the Head of AIML in IPB Tech for the end-to-end design, build, and production delivery of priority IPB AI/ML use cases, with particular focus on agentic AI applications, generative AI guardrails, and production ML supporting advisor and client journeys. Job responsibilities Owns ...

Description Purpose of the role To use innovative data analytics and machine learning techniques to extract valuable insights from the bank's data reserves, leveraging these insights to inform strategic decision-making, improve operational efficiency, and drive innovation across the organisation. Accountabilities Identification, collection, extraction of data from … python and contribute to codebases Data Manipulation - Experience querying large datasets (SQL/Pyspark) Machine learning/AI expertise - Advanced knowledge of ML/AI algorithms and their applications Financial domain knowledge - Understanding of banking products, risk frameworks, and regulations Data visualization - Ability to create compelling visual representations ...

engineer eager to grow. Join the ranks of top talent at one of the world's most influential companies.As an Applied AI ML Engineer – Associate at JPMorgan Chase within the International Private Bank (IPB) Technology Artificial Intelligence and Machine Learning (AIML) Team, you will design, develop, and deliver … Tech AIML team, reporting to the AIML Team Lead.Job responsibilitiesExecutes standard software solutions, design, development, and technical troubleshooting for the team's AI/ML productsBuilds and tests features of agentic AI, LLM-powered and ML applications under the direction of senior engineersWrites secure, high-quality production code and maintains ...

take their career to new heights. Join the ranks of top talent at one of the world's most influential companies.As an Applied AI ML Lead - Vice President at JPMorgan Chase within the International Private Bank (IPB) Technology Artificial Intelligence and Machine Learning (AIML) Team, you provide deep … responsible to the Head of AIML in IPB Tech for the end-to-end design, build, and production delivery of priority IPB AI/ML use cases, with particular focus on agentic AI applications, generative AI guardrails, and production ML supporting advisor and client journeys.Job responsibilitiesOwns end-to-end delivery ...

responsible to the Head of AI, IPB Tech for the end-to-end design, build, and production delivery of priority IPB AI/ML use cases, with particular focus on agentic AI applications, generative AI guardrails, and production ML supporting advisor and client journeys.Job responsibilitiesOwns end-to-end delivery … priority IPB AI/ML use cases, from problem framing and business case through to deployed, monitored production services with measurable advisor and client impactLeads the engineering build of agentic AI and LLM-powered products serving IPB advisors and clients across international marketsSets the engineering quality bar for the team ...

skills Formal training or certification on artificial intelligence and machine learning concepts and applied experience Advanced proficiency in Python and the modern ML/DL stack (e.g., PyTorch, Hugging Face) Hands-on experience evaluating, fine-tuning, and deploying Large Language Models Strong grounding in experimental design, evaluation … benchmarking of ML systems Ability to bridge research and engineering: prototypes that become production-ready capabilities Awareness of inference cost, performance, and optimisation techniques Strong communication skills, including translating research into business and engineering terms Published in a top-tier AIML venue (e.g. NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR ...

capabilities, and skillsFormal training or certification on artificial intelligence and machine learning concepts and applied experienceAdvanced proficiency in Python and the modern ML/DL stack (e.g., PyTorch, Hugging Face)Hands-on experience evaluating, fine-tuning, and deploying Large Language ModelsStrong grounding in experimental design, evaluation, and benchmarking … ML systemsAbility to bridge research and engineering: prototypes that become production-ready capabilitiesAwareness of inference cost, performance, and optimisation techniquesStrong communication skills, including translating research into business and engineering termsPublished in a top-tier AIML venue (e.g. NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR), or equivalent open-source/applied-research ...

understand operational challenges and translate them into scalable AI and data-driven solution architectures.Design, develop and deploy AI and Generative AI solutions, including machine learning models, data pipelines and application components that are secure, reliable and performant.Drive the operationalisation of AI solutions using modern engineering and MLOps practices … EDUCATION & EXPERIENCEDegree or equivalent experience in Computer Science, Artificial Intelligence, Data Engineering, Mathematics or a related discipline.Proven experience designing, building and deploying AI or machine learning solutions in a consulting, public sector or enterprise technology environment.Experience owning technical deliverables or workstreams, managing priorities and engaging effectively with both ...

will bring advanced engineering expertise to a collaborative, high-performing team focused on building scalable, cloud-native applications that leverage artificial intelligence and machine learning to drive smarter risk decisions. Your work will directly support the firm's ability to assess, monitor, and manage credit risk across wholesale … wholesale credit risk workflowsLead the design and implementation of cloud-native solutions, ensuring high availability, performance, and security across distributed systemsIntegrate artificial intelligence and machine learning capabilities into risk technology platforms to enhance analytical and predictive functionsDrive end-to-end software development lifecycle activities, including design, development, testing ...

innovation, and ensure our systems remain reliable and future‐ready. Job Responsibilities: Design, develop, and implement AI and data engineering solutions, including data pipelines, machine learning models, analytics applications, and Agentic AI systems. Write secure, high‐quality code in Java, applying best practices for AI and data engineering. … applications. Implement and monitor autonomous AI agents, ensuring reliability, safety, and alignment with organizational goals. Stay current with advancements in Agentic AI, reinforcement learning, and related frameworks. Required Qualifications, Capabilities, and Skills: Formal training or certification in software engineering concepts and recent applied experience in software development. Deep expertise ...

pace and become job-ready in as little as afew weeks. Our programme includes: Official AWS Certified Cloud Practitioner certification Training in Python, Machine Learning, and AI systems Hands-on projects using real-world AI tools and technologies Professional CV and LinkedIn support Interview preparation Dedicated recruitment support … cost of your training over 12 months so you can get qualified without financial pressure. Salary expectations: AI Engineer: £45,000 £60,000 Machine Learning Engineer: £60,000 £75,000 Progression into senior AI roles with higher earning potential We support you into employment We focus on outcomes ...

Data Science/ML Engineers Location - Glasgow, (Edinburgh is also fine) Duration - 6 months Onsite Requirements - 2-3 days onsite Skills Analytics Centre of Excellence is looking for experienced ML Engineer to support a new initiative focused on Transaction Monitoring (TM) for Business Banking. A similar machine learning … these capabilities into the Business Banking space. Required Skills Strong Python programming skills, including data analysis using libraries such as Pandas Strong understanding of Machine Learning, including both supervised and unsupervised techniques Experience with tree-based and boosting algorithms such as XGBoost, LightGBM, and related approaches Experience working ...

software engineering concepts, plus 5+ years of applied experience building production Python systems, including web/API services (Flask or FastAPI) and the ML/NLP ecosystem (scikit-learn, pandas, NumPy, spaCy, PyTorch or TensorFlow). Demonstrated experience taking machine learning models from prototype to production - training, packaging … Knowledge of deep learning architectures (CNNs, transformers, sequence models) and of reinforcement learning concepts and their practical applications. Experience building self-service ML tooling - model catalogues, automated pipelines, feature stores, and explainability (SHAP, LIME) surfaced to non-technical users. Understanding of industry-standard validation and testing for LLMs ...

deployment pipelines, model serving, containerisation, orchestration, and environment managementSets the standard for reliability, observability, and operational excellence across the team's production AI/ML servicesBuilds the tooling and paved paths that let AI engineers ship agentic AI and ML products safely and quicklyImplements platform-level security, secrets management … containerisation, and cloud-native deployment patternsStrong CI/CD experience and a track record of building deployment and release automationExperience serving, scaling, and monitoring ML models or data-intensive services in production (MLOps)Practical experience with observability tooling (metrics, logging, tracing) and production incident responseExperience operating ML/LLM workloads ...

pipelines, model serving, containerisation, orchestration, and environment management Sets the standard for reliability, observability, and operational excellence across the team's production AI/ML services Builds the tooling and paved paths that let AI engineers ship agentic AI and ML products safely and quickly Implements platform-level security, secrets … cloud-native deployment patterns Strong CI/CD experience and a track record of building deployment and release automation Experience serving, scaling, and monitoring ML models or data-intensive services in production (MLOps) Practical experience with observability tooling (metrics, logging, tracing) and production incident response Experience operating ML/ ...

practices (SLOs, error budgets, runbooks) and leads production incident response and post-incident review Builds and operates observability across the team's AI/ML services (metrics, logging, tracing, alerting) Automates infrastructure provisioning and configuration through infrastructure-as-code Implements operational security, secrets management, and access controls to firm-wide … environment Master's degree in Computer Science, Engineering, or a related technical field (or equivalent applied experience) Preferred qualifications, capabilities, and skills Experience operating ML/LLM workloads in production (MLOps, inference reliability, cost/performance management) Experience within financial services technology Familiarity with JPM-internal platform, cloud, and observability ...