Senior Solutions Architect, Financial Services Capital Markets

August 28

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Logo of NVIDIA

NVIDIA

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.

10,000+ employees

Founded 1993

🤖 Artificial Intelligence

🎮 Gaming

📋 Description

• What You’ll Be Doing: Partner with NVIDIA Engineering, Product, and Sales teams to secure design wins at customers. • Enable development and growth of NVIDIA product features through customer feedback and proof-of-concept evaluations. • Perform proof-of-concepts working side by side with clients, engineers, and other architects on in-depth analysis, profiling and optimization of machine learning/deep learning models to ensure the best performance on current- and next-generation GPU architectures. • Work directly with client ML researchers and developers/engineers on business-impacting workflows, projects, and issues to drive success using NVIDIA technology. • Facilitate rapid resolution of customer issues and promote the highest levels of customer satisfaction. • Build collateral (notebooks/ blogs) applied to Finance industry use-cases such as ML/DL, recommender systems, GNN, monte-carlo simulations, Quantitative Finance, etc. by working closely with customers. • What We Need To See: BS/MS/PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or other Engineering fields (or equivalent experience) • 12+ years experience as an ML/Software Engineer with a proven track record in writing code in Python, C++ • Experience with ML/DL algorithms with frameworks such as PyTorch, Spark, Dask, Jax, TensorFlow • Ability to communicate ideas and share code clearly through blog posts, GitHub • Enjoy working with multiple levels and teams across organizations (engineering/research, product, sales, and marketing teams) • Effective verbal/written communication and technical presentation skills • Self-starter with a passion for growth, a real enthusiasm for continuous learning, and sharing findings across the team • Skilled in deploying ML/DL models at scale on public cloud computing and/or on-prem HPC clusters in production • Ways To Stand Out From The Crowd: Demonstrate C/C++ programming proficiency with an understanding of software design, programming techniques, and algorithms, alongside experience performing performance optimizations. • Familiarity with NVIDIA GPU architectures. • GPU Development experience through NVIDIA CUDA-x libraries, cuBLAS, cuDNN. • Knowledge of MLOps technologies such as containers, data center deployments, cluster management software, etc. • Experience working with enterprise developers building HPC or data analytics applications.

🎯 Requirements

• BS/MS/PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or other Engineering fields (or equivalent experience) • 12+ years experience as an ML/Software Engineer with a proven track record in writing code in Python, C++ • Experience with ML/DL algorithms with frameworks such as PyTorch, Spark, Dask, Jax, TensorFlow • Ability to communicate ideas and share code clearly through blog posts, GitHub • Enjoy working with multiple levels and teams across organizations (engineering/research, product, sales, and marketing teams) • Effective verbal/written communication and technical presentation skills • Self-starter with a passion for growth, a real enthusiasm for continuous learning, and sharing findings across the team • Skilled in deploying ML/DL models at scale on public cloud computing and/or on-prem HPC clusters in production • Ways To Stand Out From The Crowd: Demonstrate C/C++ programming proficiency with an understanding of software design, programming techniques, and algorithms, alongside experience performing performance optimizations. • Familiarity with NVIDIA GPU architectures. • GPU Development experience through NVIDIA CUDA-x libraries, cuBLAS, cuDNN. • Knowledge of MLOps technologies such as containers, data center deployments, cluster management software, etc. • Experience working with enterprise developers building HPC or data analytics applications.

🏖️ Benefits

• Equity and benefits

Apply Now

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