15 of 15 Azure Machine Learning Jobs in the South East

analysis, and machine learning. Knowledge of vector database/indexes Skills in data pipeline creation, ETL processes, and working with large datasets. Experience working with Microsoft Azure services, including Azure Machine Learning, Azure Search Index, Azure Data Factory and Azure More ❯

insights. From developing robust proof-of-concepts to deploying enterprise-grade solutions, you will apply your expertise in AI engineering, cloud platforms, and technologies such as Generative AI, Azure, Databricks to embed intelligence into critical audit workflows and products. You will mentor junior engineers, promote best practices, and foster a culture of collaboration, innovation, and continuous improvement. … RESTful API design, authentication/authorization standards, and API lifecycle best practices; familiarity with Microsoft Graph API is a plus. Experience & Knowledge Requirements Good knowledge of generative AI, machine learning, deep learning, natural language processing or other relevant AI fields. Proven track record of designing, developing, and deploying AI systems in production environments. Proficient … clear and accessible manner. Qualifications: Bachelor (preferably master or PhD) in Computer Science, Artificial Intelligence, Data Science, Statistics, Engineering, or a related technical field. Advanced certifications in AI, machine learning, cloud computing or data engineering are highly advantageous - desirable Professional accounting qualification preferred, however not a requirement - desirable To discuss this or wider Technology roles with More ❯

insights. From developing robust proof-of-concepts to deploying enterprise-grade solutions, you will apply your expertise in AI engineering, cloud platforms, and technologies such as Generative AI, Azure, Databricks to embed intelligence into critical audit workflows and products. You will mentor junior engineers, promote best practices, and foster a culture of collaboration, innovation, and continuous improvement. … RESTful API design, authentication/authorization standards, and API lifecycle best practices; familiarity with Microsoft Graph API is a plus. Experience & Knowledge Requirements Good knowledge of generative AI, machine learning, deep learning, natural language processing or other relevant AI fields. Proven track record of designing, developing, and deploying AI systems in production environments. Proficient … clear and accessible manner. Qualifications: Bachelor (preferably master or PhD) in Computer Science, Artificial Intelligence, Data Science, Statistics, Engineering, or a related technical field. Advanced certifications in AI, machine learning, cloud computing or data engineering are highly advantageous - desirable Professional accounting qualification preferred, however not a requirement - desirable To discuss this or wider Technology roles with More ❯

insights. From developing robust proof-of-concepts to deploying enterprise-grade solutions, you will apply your expertise in AI engineering, cloud platforms, and technologies such as Generative AI, Azure, Databricks to embed intelligence into critical audit workflows and products. You will mentor junior engineers, promote best practices, and foster a culture of collaboration, innovation, and continuous improvement. … RESTful API design, authentication/authorization standards, and API lifecycle best practices; familiarity with Microsoft Graph API is a plus. Experience & Knowledge Requirements Good knowledge of generative AI, machine learning, deep learning, natural language processing or other relevant AI fields. Proven track record of designing, developing, and deploying AI systems in production environments. Proficient … clear and accessible manner. Qualifications: Bachelor (preferably master or PhD) in Computer Science, Artificial Intelligence, Data Science, Statistics, Engineering, or a related technical field. Advanced certifications in AI, machine learning, cloud computing or data engineering are highly advantageous - desirable Professional accounting qualification preferred, however not a requirement - desirable To discuss this or wider Technology roles with More ❯

Azure Databricks ecosystem. You'll ensure that the data platform architecture supports availability and growth targets and that the platforms leverage advances in AI and Machine Learning capability. The Person: Key to this is proactivity - they're really looking for someone who is always looking at "what's next" - are there new tools … design and delivery in a hybrid cloud environment but predominantly Azure/Databricks - Experience of pipeline orchestration management - Strong exprerience with Databricks - Experience of implementing machine learning and AI - Tooling such as Purview and Unity Catalog as well as the use of observability tools such as Monte Carlo, Fabric Monitoring and Log Analytics … Mentoring/Leading/Management experience initially with a small team but with a view that this will grow - Ideally skills in Delta Live Tables, Kafka, Azure Stream Analytics, Azure ML, PowerBI and Financial Modelling experience. More ❯

Scientist, you will be expected to: Build Agentic AI and GenAI solutions, from PoC to production, using agile methodologies and best practices. Apply advanced analytical techniques, such as machine learning, natural language processing, computer vision, and deep learning, to extract insights and generate solutions from structured and unstructured data. Build data pipelines, models, and … AI applications, using cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with stakeholders and colleagues, using data visualisation, storytelling, and … to data privacy regulations. Connect to your skills and professional experience A bachelor's degree (or equivalent) or higher in AI or equivalent. Proven experience in data science, machine learning, and AI, with a proven track record of delivering AI-driven solutions in a professional setting, using a variety of tools and techniques. Proficient in programming More ❯

Scientist, you will be expected to: Build Agentic AI and GenAI solutions, from PoC to production, using agile methodologies and best practices. Apply advanced analytical techniques, such as machine learning, natural language processing, computer vision, and deep learning, to extract insights and generate solutions from structured and unstructured data. Build data pipelines, models, and … AI applications, using cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with stakeholders and colleagues, using data visualisation, storytelling, and … to data privacy regulations. Connect to your skills and professional experience A bachelor's degree (or equivalent) or higher in AI or equivalent. Proven experience in data science, machine learning, and AI, with a proven track record of delivering AI-driven solutions in a professional setting, using a variety of tools and techniques. Proficient in programming More ❯

Scientist, you will be expected to: Build Agentic AI and GenAI solutions, from PoC to production, using agile methodologies and best practices. Apply advanced analytical techniques, such as machine learning, natural language processing, computer vision, and deep learning, to extract insights and generate solutions from structured and unstructured data. Build data pipelines, models, and … AI applications, using cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with stakeholders and colleagues, using data visualisation, storytelling, and … to data privacy regulations. Connect to your skills and professional experience A bachelor's degree (or equivalent) or higher in AI or equivalent. Proven experience in data science, machine learning, and AI, with a proven track record of delivering AI-driven solutions in a professional setting, using a variety of tools and techniques. Proficient in programming More ❯

for Argos & Nectar Products. Experience Required: MTA (Multi-Touch Attribution) and MMM (Marketing Mix Modelling) Experience Python SQL Pyspark Cloud Technology - Ideally AWS or Azure Machine Learning Experience Accumetric Metrics Experience of working with multi-functional teams Sanderson is committed to barrier-free and inclusive recruitment. We are a Disability Confident recruiter, and More ❯

months of graduation, we’ll refund 100% of your fees. What You’ll Gain - Hands-On Skills: Excel, SQL, Python, Power BI, Azure AI, Machine Learning - Industry Certifications: CompTIA Data+, Microsoft Power BI (PL-300), Azure AI Fundamentals (AI-900) - Real Projects: Work on real-world data challenges to showcase More ❯

looking for a Cloud & ML Infrastructure Engineer to join our team. You'll play a key role in designing, building, and maintaining scalable systems that power cutting-edge machine learning workloads. From cloud infrastructure to distributed training environments, you'll help lay the foundation for delivering next-generation AI solutions. Responsibilities Design, deploy, and maintain scalable … high-performance cloud-based infrastructure for ML workloads and APIs. Manage cloud platforms (AWS, Azure, GCP) including ML nodes for local development and distributed training. Install, configure, and monitor servers, ensuring smooth system performance. Optimize shared and local storage for big data ML workloads. Build and scale containerized applications using Docker, Kubernetes, Terraform, etc. Collaborate closely with … experience in a cloud infrastructure or related role (ML experience preferred). Strong scripting skills (Bash, PowerShell, Python, etc.). Hands-on experience with cloud platforms (AWS, GCP, Azure). Proficiency in containerization and orchestration (Docker, Kubernetes). Expertise in managing and optimizing cloud-based systems at scale. Preferred Skills Familiarity with Python (Jupyter) and ML frameworks More ❯

document intelligence (OCR, NER). Knowledge of ML Ops (experiment tracking, monitoring, CI/CD for ML). Familiarity with cloud AI services (AWS Sagemaker, GCP Vertex AI, Azure ML). Exposure to business process improvement or automation. If this role is of interest and you would like to learn more, please get in touch. You can More ❯

gaming and film create and interact with 3D content. They are seeking an ML & Cloud Infrastructure Engineer to design and maintain the scalable infrastructure that powers cutting-edge machine learning workloads and production systems. This is a chance to work at the forefront of AI innovation in 3D technology, with huge scope to shape the platform … and practices in a fast-moving startup environment. The role will involve: Building and maintaining scalable cloud infrastructure (AWS, GCP, Azure) for ML workloads and APIs Setting up ML nodes for distributed training and local development Managing containerised environments (Docker, Kubernetes, Terraform) Optimising storage for big data pipelines supporting ML workloads Monitoring systems and responding to incidents … 6+ years' experience in cloud engineering, ideally with ML-related workloads Proficiency in scripting (Bash, PowerShell, Python) Start-up/Scale-up Experience Strong cloud skills (AWS, GCP, Azure) and containerisation (Docker, Kubernetes) Experience in automating deployments and orchestrating cloud environments Nice to have: Python (Jupyter, PyTorch), monitoring tools (Prometheus, Grafana), cloud databases (RDS, Aurora, Spanner), CI More ❯

requirements Required Expertise: Extensive ML Ops/ML Engineering experience, particularly in assurance, governance, and monitoring Hands-on knowledge of ML Ops platforms and tools (Kubeflow, MLflow, SageMaker, Azure ML, or equivalent) Proven ability to deploy and maintain AI solutions in regulated or complex operational settings Strong grounding in responsible AI practices, including explainability and fairness Experience More ❯

NIST AI RMF, EU AI Act) and responsible AI design. Strong stakeholder skills-able to bridge the gap between business needs and technical delivery. Hands-on experience with Azure OpenAI, Azure ML, Databricks, M365 extensibility-or similar stacks. Robert Walters Operations Limited is an employment business and employment agency and welcomes applications from all More ❯