Job Overview:

CodeNinja is looking for a Mid Level Python Developer with a strong background in DevOps and expertise in Machine Learning Operations (ML/Ops). The ideal candidate will play a key role in deploying, managing, and optimizing machine learning models in production. You will be responsible for bridging the gap between data science and operations, ensuring seamless integration and deployment of ML solutions.

Key Responsibilities:

• Develop and maintain Python-based ML applications, ensuring they are robust and scalable.
• Deploy machine learning models into production environments, utilizing CI/CD practices.
• Collaborate with data scientists and engineers to streamline deployment pipelines in ML/Ops.
• Monitor and optimize the performance of deployed models, implementing necessary updates and improvements.
• Implement and manage cloud infrastructure for ML projects, leveraging platforms like AWS or Azure.
• Automate deployment processes, ensuring repeatability and efficiency.
• Participate in setting best practices for ML model reliability, reproducibility, and monitoring.

Requirements

• 5-8 years of professional experience in Python development.
• Strong understanding of DevOps principles, especially in the context of ML/Ops.
• Experience in deploying and managing machine learning models in production.
• Hands-on experience with cloud platforms (AWS, Azure, GCP) and CI/CD tools.
• Knowledge of containerization technologies (Docker, Kubernetes) for ML model deployment.
• Familiarity with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Strong problem-solving skills with the ability to work autonomously and in a team.
• Excellent communication skills, with the ability to convey technical concepts to non-technical stakeholders.

Preferred Qualifications:

• Experience with monitoring and logging tools in ML environments.
• Understanding of data pipeline management and orchestration tools.
• Exposure to machine learning model versioning and governance practices.

Benefits

• Provident Fund
• Gym Membership
• Leaves as per the company policy.
• Company-paid trips
• Easy Loan Facility for Employees
• Yearly increment
• Health Insurance (includes spouse and parents) (till the age of 80)