Overview
About NetApp
NetApp is the intelligent data infrastructure company, turning a world of disruption into opportunity for every customer. No matter the data type, workload or environment, we help our customers identify and realize new business possibilities. And it all starts with our people.
If this sounds like something you want to be part of, NetApp is the place for you. You can help bring new ideas to life, approaching each challenge with fresh eyes. We embrace diversity and openness because it's in our DNA. Of course, you won't be doing it alone. At NetApp, we're all about asking for help when we need it, collaborating with others, and partnering across the organization - and beyond.
"At NetApp, we fully embrace and advance a diverse, inclusive global workforce with a culture of belonging that leverages the backgrounds and perspectives of all employees, customers, partners, and communities to foster a higher performing organization."-George Kurian, CEO
Job Summary
NetApp is seeking an AI engineer to join the Data Services organization. The overarching vision of this organization is to empower organizations to effectively manage and 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 suite of data services. As a key AI engineer in this initiative, the candidate will be responsible for independently developing and deploying LLM-based solutions, leveraging advancements in AI to solve real-world challenges in the domains of data governance and compliance. The candidate will possess deep expertise in using modern AI/ML systems to ship impactful products to production. This is going to be a challenging and a fun role in one of the most exciting roles in the industry today.
Job Requirements
- Lead the development and deployment of AI/ML systems for Data governance 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-focused 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.
Required and Preferred Qualification
Required Qualification
- Master’s degree in computer science / applied mathematics/statistics/data science or equivalent experience.
- Strong expertise in data science fundamentals and model evaluations. Solid understanding of supervised and unsupervised machine learning algorithms (machine learning and deep learning).
- 4-8 years of experience of optimizing and shipping machine learning and deep learning models to production.
- Demonstrated proficiency in using large language models, prompting techniques, fine-tuning and knowing when not to use LLMs.
- Proficiency in Python and at least one modern ML framework such as PyTorch / Tensorflow or transformers.
- Excellent communication and collaboration skills, with a demonstrated ability to work effectively with cross-functional teams and organizational stakeholders.
Preferred Qualification
- Curiosity and tinkering with AI agents or multi-agent systems with agentic AI frameworks (Langgraph, LlamaIndex, crewai, smolagents etc.).
- Understanding of data governance, security policies, and compliance frameworks.
- Applied knowledge of MLOps / LLMOps practices, CI/CD pipelines, cloud platforms and ML systems lifecycle management.
- Experience of representing their work or company in AI/ML conferences. Publications or contributions to AI/ML community related to NLP or data governance.
- Active GitHub profile showcasing relevant open-source AI/ML projects or Kaggle achievements
At NetApp, we embrace a hybrid working environment designed to strengthen connection, collaboration, and culture for all employees. This means that most roles will have some level of in-office and/or in-person expectations, which will be shared during the recruitment process.
Equal Opportunity Employer:
NetApp is firmly committed to Equal Employment Opportunity (EEO) and to compliance with all laws that prohibit employment discrimination based on age, race, color, gender, sexual orientation, gender identity, national origin, religion, disability or genetic information, pregnancy, and any protected classification.
Did you know...
Statistics show women apply to jobs only when they're 100% qualified. But no one is 100% qualified. We encourage you to shift the trend and apply anyway! We look forward to hearing from you.
Why NetApp?
We are all about helping customers turn challenges into business opportunity. It starts with bringing new thinking to age-old problems, like how to use data most effectively to run better - but also to innovate. We tailor our approach to the customer's unique needs with a combination of fresh thinking and proven approaches.
We enable a healthy work-life balance. Our volunteer time off program is best in class, offering employees 40 hours of paid time off each year to volunteer with their favourite organizations. We provide comprehensive benefits, including health care, life and accident plans, emotional support resources for you and your family, legal services, and financial savings programs to help you plan for your future. We support professional and personal growth through educational assistance and provide access to various discounts and perks to enhance your overall quality of life.
If you want to help us build knowledge and solve big problems, let's talk.