Full Stack Engineer

Role : Full Stack Developer / Engineer - MLOpsLocation : Pune / NagpurDuratation : FulltimeWe are looking for Full Stack Developer / Engineer in MLOps to join the CBT Platform Development team. This role is critical in laying the foundation for a larger squad planned for 2026.Must have – Python / Typescript / Azure / Kubernetes / Front-end experience (React)Nice to have – MLops and .net C#Experience – 6 to 8 yearsStart Date – ASAPInterviews – 2 rounds of client interviewsInterview Approach : - Strong problem-solving skills- Approach to solving problems- Hands-on coding skills- Use of Copilot or similar tools to write code- Ability to write unit test cases- Following a modern development cycleJob Description : Seeking a highly skilled Full Stack Engineer with expertise in MLOps , Kubernetes (K8s) , Apache Airflow , Python , TypeScript , Kadro , and Azure to join our dynamic team. The ideal candidate will be responsible for designing, developing, and deploying scalable machine learning solutions and cloud-native applications, ensuring seamless integration and automation across platforms.Key Responsibilities : - Develop and maintain end-to-end full stack applications with a focus on ML deployment and automation.- Design, implement, and manage scalable MLOps pipelines utilizing Kubernetes , Airflow , and Azure .- Collaborate with data scientists and DevOps teams to automate ML workflows and deployment processes.- Build robust backend services using Python and integrate them with frontend components developed in TypeScript .- Manage container orchestration and deployment strategies using Kubernetes .- Develop and enhance cloud infrastructure and services on Azure to support scalable ML solutions.- Implement monitoring, logging, and alerting for deployed ML models and applications.- Ensure code quality, security, and best practices are followed throughout the development lifecycle.Required Skills & Qualifications : - Proven experience in Full Stack Development with proficiency in Python and TypeScript .- Strong understanding of MLOps practices and tools.- Hands-on experience with Kubernetes (K8s) for container orchestration.- Experience with Apache Airflow for workflow automation.- Solid knowledge of Azure cloud platform services and infrastructure management.- Familiarity with Kadro (or equivalent workflow / automation tools).- Experience in deploying and managing ML models in production environments.- Strong problem-solving skills and ability to work in a collaborative team environment.- Excellent communication skills and ability to adapt to evolving project requirements.Preferred Qualifications : - Experience with CI / CD pipelines and DevOps practices.- Knowledge of data engineering and database management.- Prior experience working in a cloud-native environment.RegardsVibha