Staff Data and Applied Scientist at NetApp, Inc.

Job Summary

NetApp is seeking a capable Staff Data & Applied Scientist to join the Data Services organization. The overarching vision of this organization is to empower organizations to effectively govern their data estate and build cyber-resiliency while accelerating their digital transformation journey. To get to this vision, we will embark on an AI-first approach to build and deliver world-class data services. As a key technical leader in this initiative, the Staff Data & Applied Scientist will be responsible for architecting machine learning systems, and building data pipelines and ML models across data governance and compliance domains. While overseeing the technical work of 1-3 data and machine learning engineers, the ideal candidate will also possess deep subject matter expertise in modern AI/ML systems and a demonstrated history of shipping impactful products into production. This is going to be a challenging and fun role in one of the most exciting roles in the industry today

Job Requirements

• Lead the design and implementation of ML systems for Data governance area with techniques such as classical Machine learning, Generative AI models and AI agents.
• Ensure scalability, reliability, and performance of AI models in production environments.
• Oversee ML design reviews, create best practices and playbooks for end-to-end ML systems in production.
• Collaborate with data engineers to develop scalable data pipelines for various AI/ML-driven solutions from building curated data pipelines, ML feature pipelines and deployment services.
• Work with a great deal of autonomy and be the technical thought leader in data governance product area. creating a forward-looking vision with clear direction.
• Effectively communicate complex technical artifacts to both technical (engineers & scientists) and non-technical audiences.
• Work closely with cross-functional teams including business stakeholders to innovate and unlock new use-cases for our customers that is driven through data intelligence.
• Participate in cross-functional meetings, workshops, and planning sessions to ensure data engineering activities support the overall objectives across data services and platform initiatives. 
• Coaching and leadership for data scientists and the broader cross-functional team, helping influence and develop their skills and capabilities by fostering a culture of innovation and continuous learning.
• Have a strong customer focus and build AI/ML products that delight our customers.
• Represent NetApp as a leader and ambassador in the machine learning community, building relationships with external partners and promoting the company's product capabilities in industry/academic conferences

Education and Qualifications

• Master’s or Bachelor's in computer science, Engineering, Applied Mathematics/Statistics/Data Science or equivalent skills.
• 10+ years of experience as a data and machine learning engineer, with a track record of building data/feature pipelines and shipping successful products with AI/ML & NLP capabilities at scale. Recent focus on experimenting & deploying LLMs to production is a bonus.
• Solid understanding of supervised and unsupervised machine learning algorithms and 5+ years of experience shipping them in production.
• Strong Proficiency in Python, modern ML frameworks (PyTorch, transformers) and cloud platforms.
• Applied knowledge of MLOps practices, CI/CD pipelines and ML model lifecycle management.
• Excellent communication and collaboration skills, with demonstrated ability to work effectively with cross-functional teams and stakeholders at all levels of the organization.
• (Preferred) Good understanding of data governance, security policies and compliance frameworks.
• (Preferred) Demonstrated curiosity and tinkering with AI agents or multi-agent systems.
• (Preferred) Publications or contributions to AI/ML community related to NLP or data governance.
• (Preferred) 2+ years’ experience in technically leading a team of data and machine learning engineers.
• (Preferred) Solid understanding of deep learning approaches in Natural Language Processing and Computer Vision domains.
• (Preferred) Active GitHub profile showcasing relevant ML projects or Kaggle achievements are a bonus.