31 Couchdb Jobs - Page 2

Ensure quality software delivery & enhancements. Manage full software lifecycle. Provide Tier 3+ support & implement safe changes. Specialize in an LMS functional area (e.g., Integrations, Calculations, Equipment Interfaces). Required Candidate profile CS degree & 4–8 yrs exp. in agile, coding, testing & ops. Exp. in Java 9+, JS, Ruby, REST APIs,HTML, JSON, SOLID. Skilled in TDD/BDD, Agile, Docker/K8s, SQL/NoSQL, Kafka, RabbitMQ,

Lead team of Blockchain Developers, write & review high-quality codes. Design & build Blockchain framework, accelerators & assets. Design & deploy smart contracts on Ethereum & Layer 2 sidechains. Collaborate on decentralized finance projects & TDD. Required Candidate profile B.Tech/ MCA 6+ Yrs exp in Solidity smart contract prog. Hands-on blockchain APIs, Ethereum standards (ERC-20, ERC-721) & De-Fi projects, Docker, Kubernetes, Node.js, Open-source tools, React/ Angular.

1. Utilize expertise in AI/ML and Data Science to develop and deploy AI models in production environments, ensuring scalability, reliability, and efficiency. 2. Implement and optimize machine learning algorithms, neural networks, and statistical modeling techniques to solve complex problems. 3. Hands-on experience in developing and deploying large language models (LLMs) in production environments, with a good understanding of distributed systems, microservice architecture, and REST APIs. 4. Collaborate with cross-functional teams to integrate MLOps pipelines with CI/CD tools for continuous integration and deployment. 5. Stay updated with the latest advancements in AI/ML technologies and contribute to the development and improvement of AI frameworks and libraries. 6. Communicate technical concepts effectively to non-technical stakeholders, demonstrating excellent communication and interpersonal skills. 7. Ensure compliance with industry best practices and standards in AI engineering, maintaining high standards of code quality, performance, and security. 8. Experience in using container orchestration platforms such as Kubernetes to deploy and manage machine learning models in production environments. Required education Bachelor's Degree Preferred education Bachelor's Degree Required technical and professional expertise 1. Programming Proficiency: Proficiency in Python, C++. Experience with relevant ML libraries (e.g., TensorFlow, PyTorch) for developing production-grade quality products. 2. Data Handling Skills: Skilled in integrating, cleansing, and shaping data. Expertise in various databases including open-source databases like MongoDB, CouchDB, CockroachDB. 3. DevOps Experience: Experienced in DevOps practices. Skills in Git, CI/CD pipelines (Jenkins, Travis CI, GitLab CI), and containerization (Docker, Kubernetes). 4. Open-Source Contribution: Open-source Contribution is a plus. Experience in contributing to open-source AI projects or utilizing open-source AI frameworks. 5. Problem-Solving Skills: Strong problem-solving and analytical skills. Experience in optimizing AI algorithms for performance and scalability. 6. AI Compiler/Runtime Skills: AI compiler/runtime skills would be a plus. 7. Agile Methodologies: Familiarity with Agile methodologies. Experience in Agile development of AI-based solutions. Ensuring efficient project delivery through iterative development processes Preferred technical and professional experience Proven ability to implement and optimize machine learning algorithms, neural networks, and statistical modeling techniques to solve complex problems effectively. Proficiency in distributed systems, microservice architecture, and REST APIs. Experience in collaborating with cross-functional teams to integrate MLOps pipelines with CI/CD tools for continuous integration and deployment, ensuring seamless integration of AI/ML models into production workflows. Demonstrated commitment to staying updated with the latest advancements in AI/ML technologies. Proven ability to contribute to the development and improvement of AI frameworks and libraries. Strong communication skills with the ability to communicate technical concepts effectively to non-technical stakeholders. Demonstrated excellence in interpersonal skills, fostering collaboration across diverse teams. Proven track record of ensuring compliance with industry best practices and standards in AI engineering. Maintained high standards of code quality, performance, and security in AI projects. Experience in using container orchestration platforms such as Kubernetes to deploy and manage machine learning models in production environments, ensuring efficient scalability and management of AI infrastructure.

1. Utilize expertise in AI/ML and Data Science to develop and deploy AI models in production environments, ensuring scalability, reliability, and efficiency. 2. Implement and optimize machine learning algorithms, neural networks, and statistical modeling techniques to solve complex problems. 3. Hands-on experience in developing and deploying large language models (LLMs) in production environments, with a good understanding of distributed systems, microservice architecture, and REST APIs. 4. Collaborate with cross-functional teams to integrate MLOps pipelines with CI/CD tools for continuous integration and deployment. 5. Stay updated with the latest advancements in AI/ML technologies and contribute to the development and improvement of AI frameworks and libraries. 6. Communicate technical concepts effectively to non-technical stakeholders, demonstrating excellent communication and interpersonal skills. 7. Ensure compliance with industry best practices and standards in AI engineering, maintaining high standards of code quality, performance, and security. 8. Experience in using container orchestration platforms such as Kubernetes to deploy and manage machine learning models in production environments. Required education Bachelor's Degree Preferred education Bachelor's Degree Required technical and professional expertise 1. Programming Proficiency: Proficiency in Python, C++. Experience with relevant ML libraries (e.g., TensorFlow, PyTorch) for developing production-grade quality products.2. Data Handling Skills: Skilled in integrating, cleansing, and shaping data. Expertise in various databases including open-source databases like MongoDB, CouchDB, CockroachDB.3. DevOps Experience: Experienced in DevOps practices. Skills in Git, CI/CD pipelines (Jenkins, Travis CI, GitLab CI), and containerization (Docker, Kubernetes).4. Open-Source Contribution: Open-source Contribution is a plus. Experience in contributing to open-source AI projects or utilizing open-source AI frameworks.5. Problem-Solving Skills: Strong problem-solving and analytical skills. Experience in optimizing AI algorithms for performance and scalability.6. AI Compiler/Runtime Skills: AI compiler/runtime skills would be a plus.7. Agile Methodologies: Familiarity with Agile methodologies. Experience in Agile development of AI-based solutions. Ensuring efficient project delivery through iterative development processes Preferred technical and professional experience Proven ability to implement and optimize machine learning algorithms, neural networks, and statistical modeling techniques to solve complex problems effectively. Proficiency in distributed systems, microservice architecture, and REST APIs. Experience in collaborating with cross-functional teams to integrate MLOps pipelines with CI/CD tools for continuous integration and deployment, ensuring seamless integration of AI/ML models into production workflows. Demonstrated commitment to staying updated with the latest advancements in AI/ML technologies. Proven ability to contribute to the development and improvement of AI frameworks and libraries. Strong communication skills with the ability to communicate technical concepts effectively to non-technical stakeholders. Demonstrated excellence in interpersonal skills, fostering collaboration across diverse teams. Proven track record of ensuring compliance with industry best practices and standards in AI engineering. Maintained high standards of code quality, performance, and security in AI projects.Experience in using container orchestration platforms such as Kubernetes to deploy and manage machine learning models in production environments, ensuring efficient scalability and management of AI infrastructure.

Responsibilities Watsonx Code Assistant is an exciting new offering from IBM that aims to revolutionize enterprise software development with Generative AI. We are seeking your expertise, motivation, and collaboration to take Watsonx Code Assistant to the next level. As a Application architect/Sr Fullstack Developer for Watsonx Code Assistant, you will be responsible for designing and developing components and features for this innovative platform. Required education Bachelor's Degree Required technical and professional expertise Experience: 10+ years of experience in software development. Development: Experience with Python , Node.js, and React, Ansible Microservices: Knowledge of microservices architecture and design. Source Control Management: Experience with Git. Preferred technical and professional experience AI/ML: Experience with AI/ML models and evaluation techniques, including Large Language Models, Prompt engineering. Container Orchestration: Familiarity with platforms like Kubernetes and OpenShift. Cloud Platforms: Experience with IBM Cloud, AWS, or Azure. Programming Language Analysis Databases: Experience working with SQL and No-SQL databases, including ElasticSearch, Redis, and Cloudant/CouchDB.

1. Utilize expertise in AI/ML and Data Science to develop and deploy AI models in production environments, ensuring scalability, reliability, and efficiency. 2. Implement and optimize machine learning algorithms, neural networks, and statistical modeling techniques to solve complex problems. 3. Hands-on experience in developing and deploying large language models (LLMs) in production environments, with a good understanding of distributed systems, microservice architecture, and REST APIs. 4. Collaborate with cross-functional teams to integrate MLOps pipelines with CI/CD tools for continuous integration and deployment. 5. Stay updated with the latest advancements in AI/ML technologies and contribute to the development and improvement of AI frameworks and libraries. 6. Communicate technical concepts effectively to non-technical stakeholders, demonstrating excellent communication and interpersonal skills. 7. Ensure compliance with industry best practices and standards in AI engineering, maintaining high standards of code quality, performance, and security. 8. Experience in using container orchestration platforms such as Kubernetes to deploy and manage machine learning models in production environments. Required education Bachelor's Degree Preferred education Bachelor's Degree Required technical and professional expertise 1. Programming Proficiency: Proficiency in Python, C++. Experience with relevant ML libraries (e.g., TensorFlow, PyTorch) for developing production-grade quality products. 2. Data Handling Skills: Skilled in integrating, cleansing, and shaping data. Expertise in various databases including open-source databases like MongoDB, CouchDB, CockroachDB. 3. DevOps Experience: Experienced in DevOps practices. Skills in Git, CI/CD pipelines (Jenkins, Travis CI, GitLab CI), and containerization (Docker, Kubernetes). 4. Open-Source Contribution: Open-source Contribution is a plus. Experience in contributing to open-source AI projects or utilizing open-source AI frameworks. 5. Problem-Solving Skills: Strong problem-solving and analytical skills. Experience in optimizing AI algorithms for performance and scalability. 6. AI Compiler/Runtime Skills: AI compiler/runtime skills would be a plus. 7. Agile Methodologies: Familiarity with Agile methodologies. Experience in Agile development of AI-based solutions. Ensuring efficient project delivery through iterative development processes Preferred technical and professional experience Proven ability to implement and optimize machine learning algorithms, neural networks, and statistical modeling techniques to solve complex problems effectively. Proficiency in distributed systems, microservice architecture, and REST APIs. Experience in collaborating with cross-functional teams to integrate MLOps pipelines with CI/CD tools for continuous integration and deployment, ensuring seamless integration of AI/ML models into production workflows. Demonstrated commitment to staying updated with the latest advancements in AI/ML technologies. Proven ability to contribute to the development and improvement of AI frameworks and libraries. Strong communication skills with the ability to communicate technical concepts effectively to non-technical stakeholders. Demonstrated excellence in interpersonal skills, fostering collaboration across diverse teams. Proven track record of ensuring compliance with industry best practices and standards in AI engineering. Maintained high standards of code quality, performance, and security in AI projects. Experience in using container orchestration platforms such as Kubernetes to deploy and manage machine learning models in production environments, ensuring efficient scalability and management of AI infrastructure.