As a Full-Stack DevOps Engineering Intern, you will be a key player in the entire software development lifecycle, from writing clean code for both the front-end and back-end to building and maintaining automated deployment pipelines This role is ideal for an aspiring engineer who wants to gain hands-on experience with cutting-edge technologies, including cloud infrastructure and the integration of AI/ML models NOTE - This is internship cum placement program so if you looking only for internship for academic purpose then please do not apply Currently pursuing a Bachelors degree in Computer Science, Information Technology Engineering, or a similar field Solid foundation in data structures, algorithms, software development lifecycle (SDLC), object-oriented programming, and modern agile methodologies Experience with Git for version control Familiarity with at least one back-end language, with a strong preference for Python, NodeJS or Go An understanding of containerization technologies like Docker A strong passion for AI/ML, DevOps, and automation Excellent problem-solving skills and a proactive, eager-to-learn attitude Good communication and collaboration skills Full-Stack Development: Develop and maintain scalable back-end services using Python or NodeJS or Go and front-end using React, Angular or Vuejs AI/ML Integration: Assist in integrating and deploying AI/ML models into core application features DevOps & Automation: Contribute to the development and maintenance of CI/CD pipelines using tools like GitHub Actions or Jenkins Contribute to the management of infrastructure as code using tools like Terraform or Ansible Cloud Infrastructure: Work with public cloud platforms (GCP or AWS) to deploy and manage applications and resources Version Control: Utilize Git for collaborative development and version management Collaboration: Work closely with a team of experienced engineers to design, build, and deploy new features Troubleshooting: Debug and resolve technical issues across the application stack and infrastructure
We are seeking a skilled and motivated Cloud DevOps Engineer with over 3 years of hands-on experience in building and maintaining scalable, reliable, and secure cloud infrastructure. You will be part of a dynamic team that focuses on delivering robust DevOps solutions using GCP / AWS / Azure, helping streamline CI/CD pipelines, automate infrastructure provisioning, and optimize cloud-based deployments. 3+ years of hands-on experience with DevOps tools and practices in a cloud environment. Strong experience with GCP / AWS services (Compute Engine, Kubernetes Engine, Cloud Functions, Cloud Storage, VPC, etc). Any of the Professional Cloud certification is mandatory. Proficiency with CI/CD tools and version control systems (e g, Git, GitHub/GitLab, Cloud Build). Solid scripting skills in Bash, Python, or similar languages. Experience with Docker and Kubernetes (GKE / AKS preferred). Familiarity with monitoring/logging tools such as Prometheus, Grafana, and Cloud Monitoring. Knowledge of networking, security best practices, and IAM on GCP / AWS. Experience with multi-cloud or hybrid cloud environments. Familiarity with Agile and DevOps culture and practices. Experience with serverless architectures and event-driven design patterns. Knowledge of cost optimization and GCP / AWS billing. Effective communication and overseas customer handling skills. Design, implement, and manage scalable and secure infrastructure on GCP / AWS. Develop and maintain CI/CD pipelines using tools such as Cloud Build, Jenkins, GitLab CI/CD, or similar. Implement infrastructure as code (IaC) using Terraform or Pulumi. Monitor system health and performance using GCP / AWS s operations suite (formerly Stackdriver). Automate manual processes to improve system reliability and deployment frequency. Collaborate with software engineers to ensure best DevOps practices are followed in application development and deployment. Handle incident response and root cause analysis for production issues. Ensure compliance with security and governance policies on GCP / AWS. Optimize cost and resource utilization across cloud services.
We are looking for a skilled and motivated AI/ML Engineer with 2-5 years of experience to join our team In this role, youll be instrumental in developing, deploying, and maintaining machine learning models and AI systems that solve real-world business challenges You will work closely with cross-functional teams to build innovative solutions from concept to delivery Education and Experience: A bachelors or masters degree in Computer Science, Data Science, or a related field Typically requires 2+ years of experience in AI/ML development Python: Strong proficiency in Python and its data science libraries (Pandas, NumPy, scikit-learn etc) ML/DL Frameworks: Hands-on experience with TensorFlow and/or PyTorch Google Cloud Platform: Deep knowledge of GCP services, particularly Vertex AI, BigQuery, Cloud Storage, Dataflow, and Kubernetes Engine (GKE) for containerized deployments Software Engineering: Solid understanding of software development principles, including Git for version control, RESTful APIs, and writing clean, maintainable code Excellent problem-solving and analytical skills Strong communication and teamwork abilities to work effectively in cross-functional teams A passion for continuous learning and staying current with the rapidly evolving fields of AI and cloud technology Develop and Deploy ML Models: Design, train, and evaluate machine learning and deep learning models using Python with frameworks like TensorFlow and PyTorch Youll be responsible for the entire model lifecycle, from data ingestion to deployment Utilize Google Cloud AI Services: Leverage a wide range of GCP AI and ML services to build solutions This includes using Vertex AI for model management, training, and serving, as well as pre-built APIs like the Vision AI API, Natural Language API, and Speech-to-Text API Data Engineering: Work with large datasets by using GCP data services such as BigQuery and Cloud Storage Youll build and manage data pipelines using tools like Dataflow or Dataproc to ensure data is clean, transformed, and ready for model training MLOps and Automation: Implement MLOps best practices to automate the machine learning workflow This involves creating CI/CD pipelines for models, monitoring model performance in production, and ensuring reproducibility Collaboration and Solution Design: Collaborate with data scientists, software engineers, and product managers to translate business needs into technical requirements Youll design end-to-end AI solutions that are scalable, cost-effective, and meet the companys goals Performance Optimization: Optimize models for performance, both in training and serving, by leveraging GCPs specialized hardware (like GPUs and TPUs) and distributed training capabilities
A Python Full Stack Lead Developer with hands-on experience in GCP & AWS AI services is a senior-level engineer who manages the entire software development life cycle, from front-end user interfaces to back-end logic and databases, with a specific focus on integrating AI and machine learning solutions from Google Cloud and Amazon Web Services This role requires both technical leadership and a deep understanding of cloud-based AI ecosystems Experience: A minimum of 5-8 years in full stack development, with at least 2-3 years in a lead or senior role Python Expertise: Deep proficiency in Python is a must, including experience with frameworks like Django or Flask Front-end Skills: Strong command of JavaScript, HTML, and CSS, with hands-on experience in at least one modern framework like React, Angular, or Vue js Cloud Platforms: AWS: Proven experience with AWS services, including EC2, Lambda, S3, IAM, and AI services (SageMaker, Rekognition) GCP: Proven experience with GCP services, including Compute Engine, Cloud Functions, Cloud Storage, and AI services (Vertex AI, Vision AI) Technical Leadership & Mentoring: Lead a team of developers, providing guidance, conducting code reviews, and ensuring the adoption of best practices Youll be the technical authority, making key decisions on architecture and implementation Full Stack Development: Architect, design, and build scalable web applications using Python for the back end and modern JavaScript frameworks for the front end This includes hands-on coding to develop new features, troubleshoot complex issues, and optimize application performance Cloud AI Integration: Integrate and manage AI/ML services from both Google Cloud Platform (GCP) and Amazon Web Services (AWS) This includes leveraging services like AWS SageMaker, Rekognition, and Polly, as well as GCP Vertex AI, Vision AI, and Natural Language AI Architectural Design: Design and implement robust software architectures, including serverless functions, microservices, and containerized applications using technologies like Docker and Kubernetes Data & Database Management: Work with both relational (eg PostgreSQL) and NoSQL (eg MongoDB) databases, ensuring data integrity and optimizing database performance Youll also manage data pipelines for the AI services DevOps & Deployment: Oversee the entire DevOps pipeline, from continuous integration/continuous delivery (CI/CD) to monitoring and logging Youll be responsible for deploying and managing applications on both AWS and GCP