NVIDIA seeks a highly technical, collaborative Product Manager to drive the roadmap, future product discovery, and delivery of accelerated libraries and tools for Multimodal Data Science applications on Omics technologies, with an emphasis on open source tools and community.
You will work with community developers, software and hardware developers, research scientists, and the user community to gather requirements, set product roadmaps, and provide go-to-market strategies. This role requires expert knowledge across data science, multimodal data, AI and HPC. Your multidisciplinary expertise in product management, open source development, data science applications, AI, and GPU computing will be key to NVIDIA's impact. We need a self-starter to continue our growth in biological sciences and single-cell! Do you have the rare blend of technical and product skills? If you are passionate about groundbreaking technology, we would love to learn more about you!
What you'll be doing:
Define and champion product vision, strategy, and roadmap for applied data science tools in single cell, and underlying libraries for multimodal data analysis in the life sciences.
Gather insights from key customers, developers, and partner with Product Architects, Solutions Architects, Alliance Management, and Business Development on broader market signals to set requirements and priorities.
Work closely with Engineering leads to deliver on our product roadmap.
Engage key customers, academic collaborators, bioinformatics developers, and industry partners to gather insights, validate concepts, and drive adoption.
Define the go-to-market strategies and contribute to product positioning and sales enablement.
Work with product marketing and technical marketing engineering to assist in crafting technical content that communicates products' value proposition to the world.
What we need to see:
Masters, PhD, or equivalent experience in computational biology, bioengineering, or biophysics.
8 or more years of product management experience, with proven delivery of software tools, libraries, and SDKs.
A consistent track record of collaborating on technical projects with multi-functional teams including external dependencies and collaborators
Deep expertise in applied data science, single cell technologies and bioinformatics analysis, including related emerging areas in spatial transcriptomics and microscopy.
Demonstrated understanding of data science approaches and deep learning in single cell data qc, batch integration, dimensionality reduction, clustering, differential expression analysis.
Outstanding interpersonal and communication skills, with a demonstrated ability to articulate concepts and value propositions to diverse audiences.
Ways To Stand Out From The Crowd
Hands-on contributions to multimodal data tooling used by the community, as well as an understanding of infrastructure approaches and tradeoffs (employing compute and memory, in-database approaches).
Experience with large scale data science and bioinformatics workflows and cloud deployments.
Experience in zero-to-one product ideation and delivery, productizing data science tooling and AI/ML models for biological applications.
Background with a variety of single cell omics technologies, as well as multi-species applications of omics in biomedicine, bio-manufacturing, infectious disease, or agriculture.
Strong experience with NVIDIA GPUs (CUDA) and our HPC+AI software stack.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most intelligent and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 258,750 USD.You will also be eligible for equity and benefits.
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NVIDIA is a publicly traded, multinational technology company headquartered in Santa Clara, California. NVIDIA's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, and ignited the era of modern AI.
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