Job Requirements

• Lead the development and deployment of AI/ML systems for Data protection with techniques from the realm of classical Machine learning, Generative AI and AI agents.
• Develop scalable data pipelines for various AI/ML-driven solutions from building curated data pipelines, setting up automated evals, adopting latest and greatest inferencing platforms for rapid iterations.
• Collaborate with data scientists and engineers to integrate AI into the broader products at NetApp. Effectively communicate complex technical artifacts to both technical and non-technical audiences.
• Work with a great deal of autonomy and proactively bring open-source AI innovations into our research and experimentation roadmap. Ensure scalability, reliability, and performance of AI models in production environments.
• Have a customer focus mindset and build AI/ML products that delight our customers.
• Represent NetApp as an innovator in the machine learning community and promote the company's product capabilities in industry/academic conferences.

Job Expectations

• The position is a Hybrid position, and the candidate is expected to work in NetApp Bangalore office at least two days a week. 

Required and Preferred Qualification

• Master’s degree in computer science / applied mathematics / statistics / data science or equivalent experience.
• 3+ years of experience in building MLOps pipelines, CI/CD pipelines, and ML systems lifecycle management.
• Strong knowledge of optimizing and shipping machine learning and deep learning models to production.
• Proficiency in Python, SQL and at least one cloud platform (AWS, Azure or GCP).
• Excellent communication and collaboration skills, with demonstrated ability to work effectively with cross-functional teams and stakeholders of an organization

Preferred Qualification

• 1+ years of experience in data engineering, including building and optimizing data pipelines and architectures.
• Solid understanding of data science fundamentals and model evaluations, including supervised and unsupervised machine learning algorithms (both machine learning and deep learning).
• Good understanding of cyber-security and data protection frameworks.
• Experience of representing your work or company at AI/ML conferences. 
  • Active GitHub profile showcasing relevant open-source AI/ML projects or Kaggle achievements.