26 to 50 of 59 Permanent Azure Machine Learning Jobs

practice focuses on helping clients control their data, turn it into actionable insights, and better leverage it through the use of AI and Machine Learning solutions directly embedded into business processes. We support clients across a number of industries and offer deep expertise in AI/… scale. Strong opinions on secure, resilient enterprise deployment of LLM‐powered systems; current knowledge of the latest model capabilities and AI product stacks. Machine Learning Engineering End‐to‐end ML lifecycle expertise: feature engineering, model training, evaluation and production deployment, including MLOps, monitoring and drift detection. ...

Experience running technical design workshops with senior client stakeholders and multi‐vendor delivery teams. Certifications NVIDIA certifications (NCP‐AI Infrastructure, or NVIDIA Deep Learning Institute credentials) — strongly preferred. Cloud AI/ML certification: AWS Certified Machine Learning – Specialty, Microsoft Certified: Azure AI Engineer Associate, or Google Professional Machine Learning Engineer — at least one preferred. Kubernetes: CKA or CKAD — preferred. TOGAF 9/10 or equivalent enterprise architecture certification — beneficial. Adjacent Technical Skills (Beneficial, Not Required) Depth in the specialist area above is mandatory. Experience ...

easily simplify complex concepts for senior decision‐makers Strong technical command of modern cloud infrastructure (GCP, AWS, Azure) and machine learning concepts A "hacker mindset" with a strong engineering foundation: you are a creative problem‐solver who builds robust, scalable, and efficient scripts … cloud platform (GCP, AWS, or Azure), including data storage, compute, and deployment patterns common in ML workflows Solid understanding of machine learning concepts and the ML development lifecycle — from data preparation and annotation through model training, evaluation, and deployment Demonstrated ability to lead ...

/HybridJob Type: FTEWe are seeking a highly experienced AI Consultant to design, implement, and drive enterprise-grade AI solutions on the Azure platform Microsoft AI Foundry. This role combines hands-on experience, solution architecture, and technical leadership, with responsibility for guiding teams and proactively supporting multiple … with Azure AI Search (vector and hybrid search), Azure AI Document Intelligence, and Azure Machine Learning.Ability to wire these services together into coherent, production-ready architectures not just run individual demos.Understanding of Azure security and identity ...

Technology Engineering senior leadership team, the Head of AI Engineering will lead the design, deployment, integration and continuous improvement of enterprise AI and machine learning capabilities, including ML platforms, generative AI, LLM services, feature pipelines andMLOpstooling. The roleis responsible forestablishingAI engineering standards,governanceand best practices across … fast-paced technology environment. Strongexpertisein machine learning,MLOps, generative AI, LLMs, AI platforms and cloud technologies (e.g. Microsoft Azure AI/Azure ML). Proven experience implementing AI engineering standards, deployment automation, modelmonitoringand Responsible AI frameworks. Excellent analytical, problem-solving ...

Technology Engineering senior leadership team, the Head of AI Engineering will lead the design, deployment, integration and continuous improvement of enterprise AI and machine learning capabilities, including ML platforms, generative AI, LLM services, feature pipelines and MLOps tooling. The role is responsible for establishing AI engineering … machine learning, MLOps, generative AI, LLMs, AI platforms and cloud technologies (e.g. Microsoft Azure AI/AzureML). Proven experience implementing AI engineering standards, deployment automation, model monitoring and Responsible AI frameworks. Excellent analytical, problem‐solving and stakeholder management skills. Strong written, verbal ...

regulated industriesIn addition to these core skills, you should have specialist experience in 2 or more of the following technologies:AzureWorking on Microsoft Azure PaaS and IaaS, specifically: App Services, Azure SQL Database, SQL Server, Storage, Synapse Analytics, Purview, Databricks, Azure … Data Lake Storage and other Azure services.Ability to Design, Build and deploy AI/ML models: Integrate Machine Learning into data pipelines, leverage Databricks ML and Azure ML to develop predictive models and drive business insights.Be ...

resilience patterns are consistently applied across services. People Leadership Lead and mentor a team of SRE engineers, fostering a culture of ownership, learning, and engineering excellence. Drive career development, performance management, and technical capability growth across the team. Collaborate with HR and Talent teams to build local hiring … including: Azure SQL, Cosmos DB, Application Gateway, Key Vault, Storage, DNS, Load Balancer, Virtual Machines, Azure Machine Learning, Sentinel AWS Lambda, ECS, RDS, CloudWatch Strong understanding of SRE principles (SLOs, SLIs, error budgets, incident response). Hands-on experience with ...

part of something bigger. As an Associate AI Engineer within Kainos' Workday Products division , you will support the team in productionising AI and machine learning solutions, working closely with and under the guidance of senior engineers to help integrate AI models into production systems. You will … roles. Good interpersonal skills, with enthusiasm for collaborating with cross-functional teams and communicating technical ideas clearly. Desirable Experience: BSc in Computer Science, Machine Learning, Software Engineering, or a related field Personal, academic, or internship projects demonstrating an interest in AI/ML productionisation. Familiarity with ...

Practice at Kainos, you will play a critical role in bridging the gap between data science and software engineering to productionize AI and machine learning solutions. You will work closely with data scientists, software engineers, and product teams to deliver robust, scalable AI solutions that enhance … technical requirements into actionable solutions, and communicate effectively with both technical and non-technical stakeholders. Desirable Experience: MSc or PhD in Computer Science, Machine Learning, Software Engineering, or a related field. Familiarity with Workday APIs, data structures, and integration patterns. Experience designing and implementing generative ...

Engineer within the Workday Practice at Kainos, you will bridge the gap between data science and software engineering to productionize AI and machine learning solutions. Working closely with data scientists, software engineers, and product teams, you will deliver robust, scalable AI solutions that enhance our Workday … requirements into actionable solutions, and communicate effectively with both technical and non-technical stakeholders. Desirable Experience: BSc, MSc, or PhD in Computer Science, Machine Learning, Software Engineering, or a related field. Familiarity with Workday APIs, data structures, and integration patterns. Experience designing and implementing generative ...

Engineer within the Workday Products at Kainos, you will bridge the gap between data science and software engineering to productionize AI and machine learning solutions. Working closely with data scientists, software engineers, and product teams, you will deliver robust, scalable AI solutions that enhance our Workday … requirements into actionable solutions, and communicate effectively with both technical and non-technical stakeholders. Desirable Experience: BSc, MSc, or PhD in Computer Science, Machine Learning, Software Engineering, or a related field. Familiarity with Workday APIs, data structures, and integration patterns. Experience designing and implementing generative ...

Engineer within the Workday Products at Kainos, you will bridge the gap between data science and software engineering to productionize AI and machine learning solutions. Working closely with data scientists, software engineers, and product teams, you will deliver robust, scalable AI solutions that enhance our Workday … solutions, and communicate effectively with both technical and non-technical stakeholders. Desirable qualifications Desirable experiences include: BSc, MSc, or PhD in Computer Science, Machine Learning, Software Engineering, or a related field. Familiarity with Workday APIs, data structures, and integration patterns. Experience designing and implementing generative ...

scale. Strong opinions on secure, resilient enterprise deployment of LLM-powered systems; current knowledge of the latest model capabilities and AI product stacks. Machine Learning Engineering: End-to-end ML lifecycle expertise: feature engineering, model training, evaluation and production deployment, including MLOps, monitoring and drift detection. … years in technology consulting, software engineering or AI/ML SME-level depth in at least one of: Agentic AI/LLM Engineering, Machine Learning Engineering, Platform & Cloud Engineering, or Software Engineering with strong architecture and design capability across cloud, data and AI domains. Clear, confident ...

About the role The AI & ML Engineering team accelerates the adoption of AI across the business, championing innovation while ensuring our machine learning solutions are robust, scalable, and cost-efficient. We enable teams to solve problems using existing AI tools where possible and build custom solutions … Hands‐on experience with GCP Vertex AI (model endpoints, pipelines, embeddings, vector search) or equivalent cloud‐native AI/ML platforms (e.g. AWS SageMaker, AzureML) and agent orchestration frameworks (e.g. LangChain, LangGraph, ADK). Solid understanding of MLOps – CI/CD, IaC (Terraform), experiment tracking, model registry, and monitoring. Proven ...

scale. Strong opinions on secure, resilient enterprise deployment of LLM-powered systems; current knowledge of the latest model capabilities and AI product stacks. Machine Learning Engineering End-to-end ML lifecycleexpertise: feature engineering, model training,evaluationand production deployment, includingMLOps, monitoring and drift detection. Practical knowledge … years in technology consulting, software engineering or AI/ML SME-level depth in at least one of: Agentic AI/LLM Engineering, Machine Learning Engineering, Platform & Cloud Engineering, or Software Engineering – with strong architecture and design capability across cloud,dataand AI domains. Clear, confident communicator ...

programming skills, software design patterns/best practices and practical experience applying TDD. Experience with Cloud services (AWS or Azure), Machine Learning, CI/CD and Containers would be standout.Crucially we need Engineers who have taken ownership in projects. What you've individually ...

business adoption. Working closely with IT, operational, commercial, and leadership teams, you will drive practical AI initiatives using Azure, LLMs, machine learning, and AI agents – ensuring solutions are secure, scalable, integrated, and delivering measurable business impact. The organisation is already investing heavily … concepts including VNets, Entra ID, API Gateways, Private Endpoints, and secure integrations Experience working with at least one major enterprise AI cloud platform (Azure preferred) Strong SQL skills and experience working with both structured and unstructured data Experience building AI agents, workflow automation, and tool/ ...

/Generative AI solutions in a commercial environment Strong knowledge of LLMs, RAG and modern AI architectures Python and cloud platform experience (Azure preferred) Experience integrating AI solutions into enterprise applications Ability … explain complex technical decisions to non-technical stakeholders Strong understanding of AI governance, security and best practice Desirable: Azure OpenAI Machine Learning React, React Native, Appian, Boomi or ServiceNow exposure They are looking for someone who can confidently explain not just what they ...

analytics, ML best practices, and clinical domain knowledge Research & Innovation: Lead exploration of cutting-edge techniques including causal inference, survival analysis, and federated learning for healthcare applications Stakeholder Communication: Translate complex ML concepts and clinical insights into clear recommendations for product, clinical, and executive stakeholders What … bring to HeliosX Machine Learning & Statistical Expertise Advanced proficiency in supervised/unsupervised learning, time-series forecasting, survival analysis, and causal inference methods Experience building production ML models for patient stratification, risk scoring, or personalized recommendations Strong foundation in statistical inference, experimental design ...

using platforms such as MLflow, Vertex AI, or SageMaker. Cloud AI Platforms: Demonstrated deployment of AI workloads on AWS, GCP, and/or Azure including managed ML services, scalable inference infrastructure, and vector stores. Programming & Frameworks: Strong Python proficiency; working knowledge of PyTorch or TensorFlow; applied experience ...

using platforms such as MLflow, Vertex AI, or SageMaker* Cloud AI Platforms: Demonstrated deployment of AI workloads on AWS, GCP, and/or Azure including managed ML services, scalable inference infrastructure, and vector stores* Programming & Frameworks: Strong Python proficiency; working knowledge of PyTorch or TensorFlow; applied experience ...

product What We’re Looking For 4+ years in platform/DevOps/infra Strong Kubernetes, Docker, cloud (AWS/GCP/Azure) GPU workloads/ML infra Experience designing & operating multi-tenant architectures with strict tenant isolation Familiarity with autoscaling & service isolation Experience with CI/… debugging production systems Nice to Have Security/compliance (SOC2, HIPAA) Exposure to AirFlow and MLFlow for scientific workflows MSC/PHD in Machine Learning Biotech/pharma experience Why Helical Live with top pharma High ownership, small team Work at the intersection of AI, biology ...

interestedModel Risk ManagementMLOpsModel ValidationSR 11-7Python## Job DescriptionThe ML Model Governance Lead owns the framework, processes and tooling that ensure machine learning models deployed in production are accurate, fair, compliant and monitored — a role that is rapidly becoming mandatory in regulated industries and is emerging … committee: chairing review meetings, escalating high-risk models and producing governance metrics for risk committees and regulators• Build model governance tooling: integrating MLflow, Azure ML or Databricks with governance workflows, automated testing and regulatory reportingRequired Skills & Experience:• 7+ years of model risk management, quantitative risk or ML ...

software development. You will work predominantly on customer projects, designing and delivering production-grade solutions that integrate large language models, agentic systems, and Azure AI services into real-world applications. As a senior member of the team, you will not only build - you will help define … Responsibilities: Key Delivery Responsibilities Lead the design, development, and deployment of AI-integrated solutions for client engagements using modern full stack technologies. Integrate Azure AI services (Azure OpenAI, Cognitive Services, Azure ML, AI Search) into production applications. Architect and build ...