Staff Applied Scientist
NetApp · Posted Oct 22
Hybrid cloud data services, enterprise storage, and cloud operations solutions
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About the role
NetApp's CPTO organization is seeking an Applied Scientist to bridge AI research and large-scale production systems. The role focuses on designing novel algorithmic solutions and advanced ML/DL models for complex business problems. The scientist will own the ML lifecycle from data ingestion and training through deployment and monitoring, and provide technical leadership in areas such as LLMs, RAG, and multi-modal systems.
What you will do
- Formulate complex business problems into formal mathematical frameworks
- Design, experiment with, and evaluate advanced ML models, Deep Learning architectures, and statistical methods
- 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
- Optimize model performance, latency, and resource utilization for high-throughput, low-latency production systems (e.g., distributing training, quantization, or optimizing inference graphs)
- 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
Skills used in this role
What the employer is looking for
- 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 datalake.
- Hands-on experience with code conversion tools like Git.
- Knowledge of software deployment - Docker/Kubernetes
- 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.
Benefits and support
- Flexibility to balance professional ambition with personal life
About NetApp
NetApp, Inc. is an American data infrastructure and data management company that provides unified data storage, integrated data services, and hybrid multi-cloud operations solutions to enterprise customers. Founded in 1992, the company empowers global enterprises to manage applications and data seamlessly across on-premises environments and major public clouds. NetApp specializes in intelligent data infrastructure, cyber resilience, and AI-driven data optimization.
- Industry
- Cloud Computing
- Company size
- 11700 employees
- Founded
- 1992
- Location
- San Jose, California, USA
- Funding stage
- Public Company
Funding
Public Company
Leadership
Chief Executive Officer
Executive Vice President and Chief Financial Officer
Executive Vice President and Chief Product Officer
President
Chief Technology Officer
Recent coverage
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