MLOps Engineer

Role : Full Stack Developer in MLOps

Location : Pune / Nagpur

Must have – Python / Typescript / Azure / Kubernetes / Front-end experience (React)

Nice to have – MLops and .Net C#

Experience – 6 to 8 years

Start Date – ASAP

We have an immediate and strategic requirement for a 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. The client is keen to partner with a vendor capable of providing the right-fit candidate for this current need, which will influence future squad expansion decisions.

Interview 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 cycle

Job 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.