476 to 500 of 1,252 Permanent Docker Jobs

camera image processing, computer vision, machine learning, or deep learning Design data annotation rules for machine learning Build or manage infrastructure, such as Docker, Kubernetes, Jenkins, GitHub Actions Behavior prediction, imitation learning, reinforcement learning, or end-to-end models. WHAT WE OFFER We are committed to creating a modern work ...

/Bitbucket, Gradle and CI/CD tools, e.g. TeamCity and UrbanCode Deploy. Experience with Linux/Unix. Knowledge on cloud technologies e.g. Artifactory, Docker and OpenShift. Knowledge of fixed income products, customer and broker market platforms and trading protocols desirable. This job description provides a high-level review ...

monitoring Knowledge of Concourse (writing pipelines, administering the cluster) Understanding of VMware vSphere ESXi Knowledge of Atlassian Suite Infrastructure as Code (e.g. Terraform, Ansible) Docker/Kubernetes containerisation and orchestration Elasticsearch/Kibana Cloud services (AWS or Azure) Helm charts MongoDB Experience building enterprise level web applications or services Apache ...

available. Write and maintain services in Python for infrastructure management and wallet operations. Own the integrations with third-party custodians. Build out Kubernetes and Docker deployments as we containerize more of the custody stack. Set up monitoring and alerting (Prometheus, Grafana, or equivalent) so we know about problems before customers ...

engineering, and evaluation techniques. Experience working with large, complex datasets and applying statistical analysis. Familiarity with cloud platforms (AWS, Azure, GCP) and containerization tools (Docker, Kubernetes). Experience managing data science teams and coaching team members. Problem-solving skills and ability to work independently and as a leader within cross ...

APIs and event‐driven/microservices architecture; Relational and analytical databases (e.g. PostgreSQL, ClickHouse or similar). Experience with CI/CD pipelines; Containerisation (Docker, Kubernetes preferred); Version control systems (Git). Strong knowledge of design patterns; Secure coding practices; Performance optimisation. Experience leading or mentoring engineers. Strong people management ...

/or Bicep Proven experience building and operating CI/CD pipelines for ML or GenAI workloads Practical knowledge of containerized deployments with Docker and orchestration in production settings Understanding of GenAI-specific operational challenges: model versioning, endpoint scaling, cost management, and security hardening Experience with Azure-native monitoring ...

Azure or GCP. Experience working in Agile environments using Scrum or Kanban. Familiarity with CI/CD pipelines and container technologies such as Docker and Kubernetes. The Cricket Factor At Sportradar, sport is part of who we are. For this role, an interest in cricket is highly beneficial. The ideal ...

pipeline ownership: embeddings, chunking strategy, vector databases, and context engineering LLMOpsfundamentals: eval harness design, prompt versioning, and production observability Cloud-native engineering maturity: Kubernetes, Docker, microservices, serverless, CI/CD, andIaC(Terraform or Helm) Strong Python; Java or equivalent backend language acceptable; production debugging and observability experience Quality of experience ...

pipeline ownership: embeddings, chunking strategy, vector databases, and context engineering LLMOpsfundamentals: eval harness design, prompt versioning, and production observability Cloud-native engineering maturity: Kubernetes, Docker, microservices, serverless, CI/CD, andIaC(Terraform or Helm) Strong Python; Java or equivalent backend language acceptable; production debugging and observability experience Quality of experience ...

similar; modern LLM/agent frameworks; cloud AI platforms (Amazon Bedrock, Azure OpenAI/AI Foundry, Google Vertex AI); vector databases; containerization and orchestration (Docker, Kubernetes); distributed computing. Architecture Design – end‐to‐end design of Generative and Agentic AI architectures encompassing data preprocessing, model selection, RAG pipelines, agent orchestration ...

versed in Agile methodologies, design patterns, DRY principles, Clean Code, and microservices architecture.* Technical Ecosystem: Proficient with modern DevOps and cloud tools, including Git, Docker, Kubernetes, and cloud platforms (GCP preferred).* Financial Domain Awareness: Good foundational understanding of financial products, risk management concepts, or risk methodologies (e.g., SPAN ...

Splunk, etc. Proficiency in continuous integration and continuous delivery tools (e.g., Jenkins, GitLab, Terraform, etc.), experience with container and container orchestration (e.g., ECS, Kubernetes, Docker, etc.) Experience with troubleshooting common networking technologies and issues Ability to identify and solve problems related to complex data structures and algorithms Drive to self ...

Great if you have it, fine if you don't: Any of the three areas above that isn't your main one Docker and containerised applications Building and consuming REST and GraphQL APIs Kubernetes, Terraform, or GCP Experience working with AI coding agents IoT and distributed connected hardware ...

building data ingestion or integration pipelines at scale, with attention to data quality and resilience Proficiency working with cloud infrastructure (AWS) and containerized services (Docker/ECS) Ability to own technical components end-to-end - from design through deployment and observability Strong collaboration skills with the ability to work across ...

with Kafka, RabbitMQ or other messaging technologies Experience with event-driven architectures Experience of real-time, low-latency transaction-based systems Knowledge of AWS, Docker and CI/CD practices Experience with PostgreSQL, MongoDB or BigQuery Exposure to data platforms, ETL processes or machine learning-enabled products Experience mentoring, coaching ...

pipeline ownership: embeddings, chunking strategy, vector databases, and context engineering LLMOpsfundamentals: eval harness design, prompt versioning, and production observability Cloud-native engineering maturity: Kubernetes, Docker, microservices, serverless, CI/CD, andIaC(Terraform or Helm) Strong Python; Java or equivalent backend language acceptable; production debugging and observability experience Quality of experience ...

pipeline ownership: embeddings, chunking strategy, vector databases, and context engineering LLMOpsfundamentals: eval harness design, prompt versioning, and production observability Cloud-native engineering maturity: Kubernetes, Docker, microservices, serverless, CI/CD, andIaC(Terraform or Helm) Strong Python; Java or equivalent backend language acceptable; production debugging and observability experience Quality of experience ...

management, latency, and cost tradeoffs Basic understanding of web technologies including JavaScript, HTML, and CSS Familiarity with cloud fundamentals (AWS, Azure, or GCP), containers (Docker), and CI/CD pipelines Understanding of Agile delivery fundamentals Experience with databases SQL or NoSQL Ability tovalidate, evaluate, and improve AI-generated outputs; understanding ...

model evaluation metrics, data pipelines, and the unique challenges of testing generative AI outputs. Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes) in a CI/CD environment is a big plus. Exceptional analytical skills to dissect complex problems and a keen eye for detail, ensuring ...

towards the development of the global platform Preferred qualifications, capabilities, and skills Knowledge of C#, WPF & .NET, ReactJS and Javascript. Experience with AWS, Kubernetes, Docker or other Cloud technologies Business knowledge of simple derivative products (vanilla options, variance swaps, strategies involving vanillas): how these are used, how to price them ...

hints) and JavaScript/TypeScript (full-stack development) RAG implementation experience built retrieval-augmented generation systems with vector databases MLOps & deployment hands-on with Docker, Kubernetes, CI/CD pipelines, and infrastructure-as-code Cloud platforms experience with AWS, Azure, or GCP for ML workloads and infrastructure management Exceptional communication ...

systems handling significant traffic or data volumes Performance optimisation, caching and latency reduction Designing for resilience and failure Containerisation and orchestration technologies such as Docker and Kubernetes Observability, monitoring and operating production systems Automated testing and modern engineering practices We don’t expect candidates to have worked with every technology ...

foundation of our core services. Strong Python skills are also critical. Real‐world experience with cloud ecosystems (Azure, AWS, or GCP) and containerization (Docker, Kubernetes). You should understand how production systems are deployed, monitored, and scaled. A firm grasp of concurrency, multithreading, and asynchronous programming. You know the difference ...

GitHub Copilot, Claude Code, or similar technologies. Exposure to LLMs, generative AI, AI agents, or agent orchestration frameworks. Familiarity with CI/CD, containerization (Docker), or software engineering best practices. Exposure to model governance, risk management, or MLOps practices. Experience with additional analytical tools or frameworks such as PyTorch, TensorFlow ...