Senior Quantum Applied Research Scientist, Calibration and Decoding

Nvidia

Remote

Quick summary

Work type: Remote
Location: Redmond, WASanta Clara, CA
Salary: $192,000–$304,750 / yr
Posted: 9 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $193k

This role $248k

$134k most similar roles pay here $323k

This role pays more than 87% of similar roles. Most pay $162,000–$223,187 — the shaded band above. At the midpoint, this role pays about $248k versus about $193k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 980 open roles on FindRole.

Listed pay typically runs $168,000–$270,250 across 966 roles with salary data.

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At a glance

TL;DR · Senior Quantum Applied Research Scientist, Calibration and Decoding

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As a Sr. Quantum Applied Research Scientist at NVIDIA, you will join the cutting-edge team driving advancements in accelerated computing by developing intelligent, real-time models for fault-tolerant quantum hardware. Your daily tasks include designing physics-informed data synthesis pipelines and post-trainable model architectures that enable rapid performance prediction and parameter inference without full experimental overhead. You will also apply reinforcement learning to calibration policy optimization and develop GPU-accelerated implementations to ensure scalability. The role requires expertise in machine learning, deep learning for science or physics, quantum device physics, and information science, including noise models and fault-tolerant systems. Proficiency with CUDA and NVIDIA GPUs is essential, as you will collaborate closely with Product, Engineering, and Applied Research teams to push the boundaries of accelerated quantum supercomputers.

Skills

Python CUDA NVIDIA Reinforcement Learning Deep Learning Machine Learning GPU Quantum Physics Quantum Control Pulse-Level Hardware Interfaces Synthetic Data Generation Hamiltonian Characterization Fine-Tuning LoRA QLoRA Adapters Domain Adaptation Model Architecture Design

What you'll do

Research and develop open AI models for quantum system calibration to advance the field.
Build physics-informed synthetic data generation pipelines for high-quality training data.
Develop surrogate models of quantum hardware to predict performance rapidly.
Architect real-time AI systems that account for calibration state and decoding requirements.
Apply reinforcement learning methods to optimize calibration policies continuously.
Communicate research findings and collaborate with academic and industry partners.

What we're looking for

Masters degree in Physics, Computer Science, Electrical Engineering, Applied Mathematics, or related field (Ph.D. preferred)
8+ years of high impact experience in quantum systems and AI/ML research
Expertise in machine learning for science, including model architecture design and training at scale
Strong background in quantum device physics, noise models, error mechanisms, and fault-tolerant quantum systems
Experience developing learned calibration or decoding models within real-time quantum control feedback loops
Deep expertise in reinforcement learning applied to physical systems or closed-loop control problems
Proficiency with CUDA and NVIDIA GPU programming for accelerating large-scale AI model training and inference

Post Quantum Cryptography Scientist

Booz Allen Hamilton

Washington, DC +1 42 days ago $77,600–$176,000

Python Rust C++ Linux Windows Cloud architectures Key management strategies Digital forensics Secure software development Penetration testing CI/CD Post-Quantum Cryptography

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