226 to 250 of 864 Remote Containerisation Jobs

. Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. Knowledge of containerization and orchestration tools (Docker, Kubernetes). Experience integrating ML models into production environments via APIs or microservices. Excellent problem-solving, analytical, and communication skills. Preferred Qualifications Bachelor’s or Master More ❯

. Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. Knowledge of containerization and orchestration tools (Docker, Kubernetes). Experience integrating ML models into production environments via APIs or microservices. Excellent problem-solving, analytical, and communication skills. Preferred Qualifications Bachelor’s or Master More ❯

. Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. Knowledge of containerization and orchestration tools (Docker, Kubernetes). Experience integrating ML models into production environments via APIs or microservices. Excellent problem-solving, analytical, and communication skills. Preferred Qualifications Bachelor’s or Master More ❯

. Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. Knowledge of containerization and orchestration tools (Docker, Kubernetes). Experience integrating ML models into production environments via APIs or microservices. Excellent problem-solving, analytical, and communication skills. Preferred Qualifications Bachelor’s or Master More ❯

. Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. Knowledge of containerization and orchestration tools (Docker, Kubernetes). Experience integrating ML models into production environments via APIs or microservices. Excellent problem-solving, analytical, and communication skills. Preferred Qualifications Bachelor’s or Master More ❯

a Software Engineer, ideally in Python (3.10+). Proven experience developing cloud-native applications (GCP or AWS). Strong understanding of CI/CD pipelines (e.g. GitHub Actions) and containerisation (Docker). Experience designing scalable, secure systems using modern principles (SOLID, TDD). Familiarity with databases (SQL, NoSQL, or graph) and API integrations. Excellent communicator who thrives in a collaborative More ❯

a Software Engineer, ideally in Python (3.10+). Proven experience developing cloud-native applications (GCP or AWS). Strong understanding of CI/CD pipelines (e.g. GitHub Actions) and containerisation (Docker). Experience designing scalable, secure systems using modern principles (SOLID, TDD). Familiarity with databases (SQL, NoSQL, or graph) and API integrations. Excellent communicator who thrives in a collaborative More ❯

ML pipelines and vector databases (e.g. Pinecone, FAISS, Weaviate). Proficiency in Python plus at least one other backend language (TypeScript or Java preferred). Proven experience with AWS , containerisation, and infrastructure as code (Terraform, Docker). Solid understanding of API design, data modelling, and microservice architecture. Excellent communication skills, with the ability to translate technical outcomes into business impact. More ❯

ML pipelines and vector databases (e.g. Pinecone, FAISS, Weaviate). Proficiency in Python plus at least one other backend language (TypeScript or Java preferred). Proven experience with AWS , containerisation, and infrastructure as code (Terraform, Docker). Solid understanding of API design, data modelling, and microservice architecture. Excellent communication skills, with the ability to translate technical outcomes into business impact. More ❯

a Software Engineer, ideally in Python (3.10+). Proven experience developing cloud-native applications (GCP or AWS). Strong understanding of CI/CD pipelines (e.g. GitHub Actions) and containerisation (Docker). Experience designing scalable, secure systems using modern principles (SOLID, TDD). Familiarity with databases (SQL, NoSQL, or graph) and API integrations. Excellent communicator who thrives in a collaborative More ❯

a Software Engineer, ideally in Python (3.10+). Proven experience developing cloud-native applications (GCP or AWS). Strong understanding of CI/CD pipelines (e.g. GitHub Actions) and containerisation (Docker). Experience designing scalable, secure systems using modern principles (SOLID, TDD). Familiarity with databases (SQL, NoSQL, or graph) and API integrations. Excellent communicator who thrives in a collaborative More ❯

a Software Engineer, ideally in Python (3.10+). Proven experience developing cloud-native applications (GCP or AWS). Strong understanding of CI/CD pipelines (e.g. GitHub Actions) and containerisation (Docker). Experience designing scalable, secure systems using modern principles (SOLID, TDD). Familiarity with databases (SQL, NoSQL, or graph) and API integrations. Excellent communicator who thrives in a collaborative More ❯

Full Stack Engineer Essential Skills Frontend: React, TypeScript, data visualisation experience. Backend: Node.js, Prisma, Fastify or similar; PostgreSQL; Caching with Redis. Cloud/DevOps: AWS, Terraform, CI/CD, containerization with Docker. Languages: Python familiarity for data tooling. Practices: Code reviews, Git, testing, deployments, observability. Strong written and spoken English. Desirable Skills Working knowledge of the following: Data visualization libraries More ❯

in defining and implementing cloud infrastructure standards and best practices. Infrastructure as Code (IaC): Knowledge of IaC tools like Terraform or CloudFormation to provision and manage infrastructure resources programmatically. Containerisation and Orchestration: Proficient with container technologies like Docker and container orchestration platforms such as Kubernetes. Automation: Strong scripting skills (e.g., Python, PowerShell) and the ability to automate routine tasks and More ❯

infrastructure, including services such as EC2, S3, RDS, Lambda, and VPC. Strong expertise in Infrastructure as Code (IaC) tools such as Terraform or AWS CloudFormation. Hands-on experience with containerization technologies like Docker, ECS, or Fargate. Proficiency in scripting languages such as Python, Bash, or PowerShell to automate tasks and workflows. Experience supporting large-scale, customer-facing SaaS environments with More ❯

a strong desire to learn and apply AI methodologies in your work. · Familiarity with front-end JavaScript frameworks (e.g., React, Vue.js). · Knowledge of cloud platforms (particularly AWS) and containerisation (Docker). Why Join Us? The Jaywing & Stubben Edge Advantage · Become an AI Practitioner: Move beyond theory. This role offers practical, career-defining experience with agentic AI frameworks—one of More ❯

a strong desire to learn and apply AI methodologies in your work. · Familiarity with front-end JavaScript frameworks (e.g., React, Vue.js). · Knowledge of cloud platforms (particularly AWS) and containerisation (Docker). Why Join Us? The Jaywing & Stubben Edge Advantage · Become an AI Practitioner: Move beyond theory. This role offers practical, career-defining experience with agentic AI frameworks—one of More ❯

scripting languages like YAML, JSON, or Python Experience with version control systems, preferably Git Proficiency in tools such as Terraform, Ansible, or AWS CloudFormation Good to have knowledge of containerization technologies such as Docker and Kubernetes Ability to work in an Agile environment and adapt to changing requirements How we'll support you Training and development to help you excel More ❯

Proficiency with SQL (Postgres/MySQL) and a NoSQL/Key-Value store (e.g., DynamoDB/Redis) * CI/CD (GitHub Actions/GitLab/CircleCI), automated testing, and containerization ( Docker ) * Demonstrated work in a commercial setting with data-intensive or ML-adjacent systems (e.g., pipelines, model serving, feature stores, analytics workloads) Nice to Have: * Experience integrating Python ML services More ❯

data programming frameworks. • Comfortable writing efficient SQL and debugging on cloud warehouses like Databricks SQL or Snowflake. • Experience with cloud infrastructure like AWS or Azure. • Experience with Linux and containerisation (e.g Docker, shell scripting). • Understanding Data modelling and Data Cataloguing principles. • Understanding of Data Management principles (security and data privacy) and how they can be applied to Data Engineering More ❯

data programming frameworks. • Comfortable writing efficient SQL and debugging on cloud warehouses like Databricks SQL or Snowflake. • Experience with cloud infrastructure like AWS or Azure. • Experience with Linux and containerisation (e.g Docker, shell scripting). • Understanding Data modelling and Data Cataloguing principles. • Understanding of Data Management principles (security and data privacy) and how they can be applied to Data Engineering More ❯

data programming frameworks. • Comfortable writing efficient SQL and debugging on cloud warehouses like Databricks SQL or Snowflake. • Experience with cloud infrastructure like AWS or Azure. • Experience with Linux and containerisation (e.g Docker, shell scripting). • Understanding Data modelling and Data Cataloguing principles. • Understanding of Data Management principles (security and data privacy) and how they can be applied to Data Engineering More ❯

data programming frameworks. • Comfortable writing efficient SQL and debugging on cloud warehouses like Databricks SQL or Snowflake. • Experience with cloud infrastructure like AWS or Azure. • Experience with Linux and containerisation (e.g Docker, shell scripting). • Understanding Data modelling and Data Cataloguing principles. • Understanding of Data Management principles (security and data privacy) and how they can be applied to Data Engineering More ❯

Practices Test Driven Development and is comfortable with various test frameworks and concepts. A proven record in developing scalable, highly available and highly performing middle-tier components. Familiarisation with containerisation and tools like Docker and Kubernetes Experience of developing, deploying, and maintaining Cloud-Based solutions on AWS Understand principles behind highly performing web pages Experience/Familiarity with Entity framework More ❯

with JSON, as well as with GraphQL Thorough understanding of CI/CD pipelines Practices Test Driven Development and is comfortable with various test frameworks and concepts. Familiarisation with containerisation and tools like Docker, ECS or Kubernetes Experience of developing, deploying, and maintaining Cloud-Based solutions on AWS Understand the principles behind what makes a high performing web page Experience More ❯