1 to 25 of 27 Machine Learning Jobs in Lanarkshire

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 ...

databases and other business applications. Develop straightforward and user-friendly AI applications for web and Microsoft Teams. Develop and deploy LLM and machine learning solutions into production environments. Implement monitoring, logging and audit processes to support GDPR, ISO and wider security requirements. Work with internal stakeholders to understand … within the business. Ensure solutions are secure, scalable, maintainable and aligned with company standards. Essential Experience 2-4 years' experience in AI/ML, software engineering or a closely related field. Experience deploying LLM or machine learning solutions into production. Strong programming skills in Python and/ ...

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 ...

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 ...

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 ...

Junior AI Engineer/Machine Learning Engineer no experience needed From £40,000 - £65,000 *This is a self-funded career programme with a guaranteed job on completion or 100% of your course fees back* Train. Certify. Get Hired. AI is expected to generate 170 million jobs … Data+ CompTIA DataAI Practical, real-world project work designed to help you develop hands-on skills Dedicated 1-to-1 tutor support throughout your learning journey CV support, interview preparation, and career coaching Access to our employer network and recruitment partners Starting Salaries Upon successful completion of the programme ...

AIML Data Platforms and Chief Data and Analytics Team , you will lead a team of 3-7 SRE engineers and scale the AI/ML Data Platform, deliver advanced technology products focused on data and analytics. You will tackle complex cloud data platform challenges, especially around Data Lake Tools. … operational excellence. Performs platform design, set-up and configuration, workspace administration, resource monitoring, providing engineering support to Data Engineering teams, Data Science/ML, and Application/Integration teams. Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions ...

Architecture capabilities: Master and Reference Data Management, Data Quality, Metadata Management, Data Taxonomy, Data Integration, Data Migration, and Data Modeling. Demonstrated proficiency in AI, machine learning, or related techniques as applied to architecture or software engineering disciplines. Hands-on experience with object-oriented software development using languages such ...

line of code, but you understand the platform end-to-end and own outcomes. You'll partner closely with product owners, data scientists and machine learning engineers, site reliability engineering, and business stakeholders to deliver stable, scalable cloud-native analytics. Job responsibilities Own application governance and records ...

integration/continuous delivery, application resiliency, and security Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) Experience with DevOps and Site Reliability Engineering principles Preferred qualifications, capabilities, and skills Familiarity with VMware, OpenShift, Hyper ...

resiliency, and security Overall knowledge of the Software Development Life Cycle Curiosity and foundational understanding of Generative AI, large language models, and AI/ML solutions Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ...

Python and/or PySpark Advanced knowledge of software application development and technical processes, with depth in disciplines such as cloud, AI/ML, or data engineering Experience in large-scale data processing, microservices, API design, Kafka, Redis, MemCached, observability tools (Dynatrace, Splunk, Grafana), and orchestration frameworks (Airflow, Temporal) Advanced ...

Expertise in Python and/or PySpark Knowledge of software application development and technical processes, with depth in disciplines such as cloud, AI/ML, or data engineering Experience in large-scale data processing, microservices, API design, Kafka, Redis, MemCached, observability tools (Dynatrace, Splunk, Grafana), and orchestration frameworks (Airflow, Temporal ...

qualifications, capabilities, and skills: Good understanding of operating systems such as Windows, Linux (Redhat/Ubuntu) Good understanding of LLM and other AI/ML frameworks which can be used in AIOPS ABOUT US J.P. Morgan is a global leader in financial services, providing strategic advice and products ...

/CD, application resiliency, and security Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile) In-depth knowledge of the financial services industry and their IT systems Practical cloud-native experience Hands-on experience using enterprise-authorized … both SQL and NoSQL databases Experience working with private and public cloud environments Familiarity with Agile and Kanban methodologies Exposure to AI/ML concepts and their application within engineering workflows ABOUT US J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world ...

making platforms measurably better, you'll find meaningful impact and growth here. As a Lead Software Engineer at JPMorgan Chase in the AI and Machine Learning Platform team, you will build and scale AI infrastructure that modernizes traditional infrastructure management and site reliability engineering through applied AI. ...

making platforms measurably better, you'll find meaningful impact and growth here. As a Senior Lead Software Engineer at JPMorganChase within the AI and Machine Learning Platform team, you will build and scale AI infrastructure that modernizes traditional infrastructure management and site reliability engineering through applied AI. ...

development skills Hands-on Google Cloud Platform (GCP) experience, building and operating cloud-native workloads Expertise in cloud architecture, distributed systems, security, AI/ML or platform engineering Advanced programming expertise in Go and/or Python Kubernetes platform engineering experience, including CRDs and API extensions. Strong knowledge of Kubernetes ...

effective risk mitigation strategies Demonstrated ability to provide deep technical insights related to software, hardware, infrastructure, and emerging technologies such as artificial intelligence and machine learning Skilled at influencing executive-level strategic decision-making and translating complex technology insights into actionable business strategies for senior leadership Strong data ...

easy-to-use online platform. Step 2: Full-Stack AI Mastery Dive deeper with in-demand technical skills including Python programming, data handling, machine learning, and version control with Git and GitHub. You’ll work on hands-on mini projects that mirror real-world challenges, helping you build ...

through to being qualified to work in a junior Data Scientist role. Through the interactive courses, you will gain knowledge in Python, R, Machine Learning, AI , and much more. You will also complete mini projects to gain practical experience and test your skills while you study. Step ...

capabilities, and skills Practical experience delivering system design, application development, testing, and operational stability at enterprise scale Experience designing and deploying production AI/ML systems, including LLM-based applications and agentic architectures in regulated environments Proficiency in one or more programming languages, particularly Python and/or PySpark Advanced … knowledge of software application development and technical processes in disciplines such as cloud, AI/ML, or data engineering Experience in large-scale data processing, microservices, API design, and orchestration frameworks Working knowledge of relational and NoSQL databases, vector stores, and data lake architectures Familiarity with observability tools and frameworks ...

aspects of the Software Development Life Cycle, including design, development, testing, and operational stability in production environments Practical understanding of AI/ML concepts and experience integrating or embedding AI/ML capabilities into business applications or data workflows, with the ability to identify opportunities where intelligent automation or predictive ...