Senior Solutions Architect, Data Platform GTM

🔥 1 minute ago

🏄 California, New York, +2 more states – Remote

🏄 California – Remote 🗽 New York – Remote 🤠 Texas – Remote ☕ Washington – Remote

💵 $184k - $287.5k / year

⏰ Full Time

🟠 Senior

💻 Solutions Engineer

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🤖 Artificial Intelligence

🎮 Gaming

Artificial Intelligence • Gaming • Automotive

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• Drive technical GTM with Data Platform ISVs across query engines, databases, analytics platforms, data processing frameworks, and AI data infrastructure. • Partner with ISVs on discovery, architecture reviews, technical deep dives, POCs, benchmarks, demos, and customer-facing enablement • Help ISVs identify the right NVIDIA acceleration paths for their platforms and use cases, including cuDF, Spark RAPIDS, Polars, Velox, cuVS, and related NVIDIA libraries • Build repeatable GTM assets such as reference architectures, technical playbooks, demos, blogs, talks, and customer training • Support emerging data platform use cases for GenAI, including unstructured data processing, RAG pipelines, data preparation, and retrieval workflows • Travel up to 20% for conferences and customers may be required

🎯 Requirements

• BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience) • 8+ years of hands-on experience with Machine Learning, Deep Learning and Data Analytics • Strong background in data platforms, distributed systems, analytics, databases, or systems for managing and processing data • Familiarity with data ecosystems such as Spark, Pandas, Polars, DuckDB, Trino, Presto, Velox, vector databases, or unstructured data pipelines • Experience working with ISVs, partners, or enterprise customers in a solutions architecture or field engineering role • Excellent presentation, communication and collaboration skills

🏖️ Benefits

• Eligible for equity and benefits