1,301 to 1,325 of 3,009 Remote Azure Jobs

ownership of demand delivery Provide technical guidance for team members Providing 2nd or 3rd level technical support About You Experience using SQL, SQL Server DB, Python & PySpark Experience using Azure Data Factory Experience using Data Bricks and Cloudsmith Data Warehousing Experience Project Management Experience The ability to interact with the operational business and other departments, translating technical concepts and More ❯

an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a passion for platform disciplines. Hands-on experience with cloud platforms (AWS, GCP, or Azure), including large-scale ML infrastructure management. Knowledge of GPU computing for model training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD More ❯

an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a passion for platform disciplines. Hands-on experience with cloud platforms (AWS, GCP, or Azure), including large-scale ML infrastructure management. Knowledge of GPU computing for model training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD More ❯

an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a passion for platform disciplines. Hands-on experience with cloud platforms (AWS, GCP, or Azure), including large-scale ML infrastructure management. Knowledge of GPU computing for model training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD More ❯

an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a passion for platform disciplines. Hands-on experience with cloud platforms (AWS, GCP, or Azure), including large-scale ML infrastructure management. Knowledge of GPU computing for model training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD More ❯

an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a passion for platform disciplines. Hands-on experience with cloud platforms (AWS, GCP, or Azure), including large-scale ML infrastructure management. Knowledge of GPU computing for model training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD More ❯

an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a passion for platform disciplines. Hands-on experience with cloud platforms (AWS, GCP, or Azure), including large-scale ML infrastructure management. Knowledge of GPU computing for model training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD More ❯

an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a passion for platform disciplines. Hands-on experience with cloud platforms (AWS, GCP, or Azure), including large-scale ML infrastructure management. Knowledge of GPU computing for model training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD More ❯

an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a passion for platform disciplines. Hands-on experience with cloud platforms (AWS, GCP, or Azure), including large-scale ML infrastructure management. Knowledge of GPU computing for model training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD More ❯

an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a passion for platform disciplines. Hands-on experience with cloud platforms (AWS, GCP, or Azure), including large-scale ML infrastructure management. Knowledge of GPU computing for model training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD More ❯

an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a passion for platform disciplines. Hands-on experience with cloud platforms (AWS, GCP, or Azure), including large-scale ML infrastructure management. Knowledge of GPU computing for model training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD More ❯

an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a passion for platform disciplines. Hands-on experience with cloud platforms (AWS, GCP, or Azure), including large-scale ML infrastructure management. Knowledge of GPU computing for model training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD More ❯

an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a passion for platform disciplines. Hands-on experience with cloud platforms (AWS, GCP, or Azure), including large-scale ML infrastructure management. Knowledge of GPU computing for model training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD More ❯

and supporting go-to-market strategies. Excellent written and verbal communication skills, with the ability to translate complex technical topics to both technical and non-technical stakeholders. AWS/Azure/GCP certifications, CISSP, CISM, or other security certifications are a plus Generous equity plan. Remote-first working environment with travel to our Oslo office and customer sites across More ❯

translating business requirements into technical requirements and in coordinating and executing IGA tool implementations (preferably Sailpoint, Omada, Saviynt or Entra) Technical Skills: Good understanding of networking infrastructure & segmentations (i.e., Azure, Entra, Active Directory, SQL) and standard protocols (i.e., SCIM, REST, SOAP) People Skills: You are a collaborative, proactive and (creative) problem solver and independent thinker who brings high accountability More ❯

least 3-5 years in a people leadership role. Expertise in AI, machine learning, deep learning, and predictive analytics. Strong proficiency in AI frameworks, cloud AI platforms (AWS, GCP, Azure), and MLOps practices. Solid understanding of AI ethics, governance, and compliance in a corporate setting. Proven track record of leading AI teams and managing AI projects. Strong strategic thinking More ❯

Finance Industry. Integration experience with APIs, web services, event streaming and messaging (Kafka, JMS, SQS etc). Experience with market-leading SaaS or iPaaS solutions. Hands-on AWS/Azure/Google Cloud experience. Database experience, including with reporting systems/data warehousing. Performance analysis, with tools like JProfiler/CodeGuru. Knowledge of Containers (Docker). Knowledge of and More ❯

Deep technical knowledge (e.g. .NET CLR internals, advanced SQL tuning). Experience with event driven architectures, event sourcing, or data streaming. Familiarity with tools in our ecosystem: Elastic, Kurrent, Azure, Pulumi. Broad exposure to multiple programming frameworks or languages. About Clio At Clio, we are on a mission to transform the legal experience for all. As the world's More ❯

core Go requirement. Strong, demonstrable experiefnce with real-time, low-latency data processing. You obsess over milliseconds and understand the trade-offs. Proficiency with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Kubernetes, Docker). Deep understanding of API design (REST, gRPC, Webhooks) and API security (OAuth 2.0, mTLS, JWTs). Knowledge of (or deep, demonstrable curiosity about More ❯

core Go requirement. Strong, demonstrable experiefnce with real-time, low-latency data processing. You obsess over milliseconds and understand the trade-offs. Proficiency with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Kubernetes, Docker). Deep understanding of API design (REST, gRPC, Webhooks) and API security (OAuth 2.0, mTLS, JWTs). Knowledge of (or deep, demonstrable curiosity about More ❯

based systems. API testing using tools such as Postman or Insomnia. In-depth understanding of QA process and software development life cycle. Understanding CI/CD pipelines such as Azure DevOps or GitHub Actions. Working knowledge of SQL. Preferred skills Experience of test automation platforms — ideally Playwright. Knowledge of Angular and TypeScript/JavaScript. Basic knowledge of cloud platforms More ❯

knowledge of IAM protocols (LDAP, SAML, OAuth, OpenID Connect). Proficiency in cross-platform scripting (e.g., T-SQL, PowerShell, Bash) and integration with on-premise/cloud directory services (Azure AD, GSuite, LDAP). Deep understanding of legacy and modern authentication protocols, access controls, and identity lifecycle management. Strong security awareness and familiarity with standards such as ISO27001, NIST More ❯

you'll be working with: EKS & AWS Lambda (Node.js) - powering our services OrgFormation - managing our AWS landing zone Instana - monitoring everything that matters ArgoCD - deploying our applications with ease Azure EntraID - managing identities securely Elastic - shipping and analyzing logs CloudFormation & Terraform - infrastructure as code PagerDuty - keeping us alert and responsive Essential skills To succeed here, you'll need some More ❯

effectively manage key stakeholders. Knowledge of common application technologies e.g. S/4 Hana, Oracle ERP, MS Dynamics, Blackline, Workday, Knowledge of common infrastructure technologies e.g. AWS, Google Cloud, Azure, SQL Database, Oracle database, MS Active Directory Industry specific risk and controls expertise e.g. Financial Services. Experience with specific regulations e.g. EU AI act, Sarbans Oxley. Holding or eligible More ❯

years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 8 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders More ❯