Staff Data Scientist

NetApp, Inc.; Bengaluru; Hybrid; INR 3,500,000 - 6,000,000; Full time

Job summary

NetApp, Inc. is seeking an Applied Scientist to bridge AI research with large-scale production systems in the CPTO team. You will design and iterate on novel algorithmic solutions, beyond off-the-shelf models, to tackle complex business problems with scalable ML pipelines.

The role emphasizes research, prototyping-to-production, and technical leadership aimed at delivering high-performance data infrastructure and AI-enabled features for NetApp customers.

Qualifications

• 12-15 years of hands-on data science and analytics experience.
• Bachelor's or Master's in Computer Science or equivalent.
• Familiarity with system software design and Unix/Linux programming.

Responsibilities

• Research and design��formulate complex business problems into mathematical frameworks.
• Prototype to production: write clean, scalable code and own model lifecycles.
• Scale and optimize: improve performance, latency, and resource use in production systems.
• Technical leadership: mentor engineers and stay current with AI research.

Skills

System software design

Multithreaded programming

Unix/Linux programming

AI/ML experience

Algorithms and data structures

Software engineering best practices

Cross-functional collaboration

Deployment understanding

Education

Bachelor's/Master's in Computer Science or equivalent

Tools

Git

Docker/Kubernetes

Prometheus/NoSQL

Job description

Job Summary

Are you ready to elevate your career in software engineering? NetApp is seeking Software Engineers to join the CPTO team and contribute to the development and design of innovative incubation projects that will drive the tech strategy for NetApp.

RoleOverview

CPTO is looking for an Applied Scientist who is passionate about bridging the gap between AI research and large-scale production systems. In this role, you will not just apply off-the-shelf models; you will design, build, and iterate on novel algorithmic solutions to complex, ambiguous business problems.

Job Requirements

• Familiarity with the design and development of system software.
• 12+ years of hands-on experience in coding of AI/ML.
• Knowledge of Unix/Linux System Programming and Multithreaded programming.
• Expertise in algorithms, data structures, and multi-threaded programming is essential.
• Commitment to sound software engineering practices and a passion for quality.
• Proven track record of meeting tight deadlines without sacrificing quality.
• Strong communication skills, both written and oral, targeted at a wide variety of internal and external audiences.
• Ability to understand customer deployment scenarios and experience in collaborating with peer teams outside of engineering.
• Familiarity with database technologies such as NoSQL, Prometheus and data lake.
• Hands-on experience with code conversion tools like Git.
• Knowledge of software deployment - Docker/Kubernetes

Key Responsibilities:

Research & Design:Formulate complex business problems into formal mathematical frameworks
Design, experiment with, and evaluate advanced ML models, Deep Learning architectures, and statistical methods

Prototyping to Production:Write clean, maintainable, and scalable code
Own the end-to-end lifecycle of ML models, from data ingestion and training to deployment and post-launch monitoring

Scale & Optimize:Optimize model performance, latency, and resource utilization for high-throughput, low-latency production systems (e.g., distributing training, quantization, or optimizing inference graphs)

Technical Leadership:Stay at the forefront of AI research (LLMs, Retrieval-Augmented Generation (RAG), vector intelligence, multi-modal systems).
Mentor junior engineers and scientists, and foster a data-driven engineering

Education

• IC - Typically requires a minimum Bachelor/Master of Engineering in Computer Science; or equivalent experience.
• 12-15 years of hands-on experience in Data Science and related analytics disciplines.

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 federal, state and local laws that prohibit employment discrimination based on age, race, color, gender, sexual orientation, gender identity, national origin, religion, disability or genetic information, pregnancy, protected veteran status, and any other protected classification.

Why You'll Thrive at NetApp

At NetApp, you won't wait for the perfect moment—you'll make it. The early planning, the extra thought, the bold idea that turns good into great: That's how our people operate and how we continue to push the boundaries of data infrastructure.

NetApp is the trusted partner for organizations transforming data into opportunity. As the only enterprise-grade storage service natively embedded in Google Cloud, AWS, and Microsoft Azure, we empower customers to run everything from traditional workloads to enterprise AI with unmatched performance, resilience, and security.

Our culture

We celebrate mold breakers, bold thinkers, and problem solvers. We reward initiative, impact, and ownership. We provide flexibility so you can balance professional ambition with your personal life. Here, differences are not just welcomed—they drive everything we do.

Submitting an Application

To ensure a streamlined and fair hiring process for all candidates, our team only reviews applications submitted through our company website. This practice allows us to track, assess, and respond to applicants efficiently. Emailing our employees, recruiters, or Human Resources personnel directly will not influence your application.

AI Disclosure

For select roles, some stages of our hiring process may use artificial intelligence tools to help evaluate applications and candidate selection. These tools support- rather than replace- human decision-making.