Senior Applied Research Engineer, Accelerator Algorithms

NVIDIA Gruppe; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

NVIDIA seeks a Senior Applied Research Engineer to drive algorithms for the Programmable Vision Accelerator (PVA) across NVIDIA DRIVE, Jetson and IGX platforms. You will analyze real-world autonomous vehicle and physical AI workloads to identify workloads suited to PVA and translate them into optimized algorithms.

You will build prototypes, benchmarks, and performance models, collaborate with internal teams and customers, and publish technical findings to advance PVA hardware, software, and

Qualifications

• BS/MS or PhD in CS, EE, Robotics or related field, or equivalent experience.
• 12+ years of experience in applied research or accelerator algorithms.

Responsibilities

• Research and characterize AV and physical AI workloads to identify algorithms for PVA.
• Develop and optimize PVA algorithms using instruction-level parallelism and vectorization.
• Translate workload insights into PVA hardware/SDK requirements.
• Build prototypes, benchmarks, and performance models for PVA.
• Leverage AI-assisted tools to accelerate workload analysis and benchmarking.
• Collaborate with internal teams and customers to integrate PVA-accelerated algorithms.
• Publish and communicate findings across research and engineering teams.

Skills

C++

Python

CUDA

DSP

SIMD

VLIW

Fixed-point

Memory hierarchy

Performance optimization

Communication skills

Technical judgment

Education

BS/MS/PhD in CS/EE/Robotics or related

Tools

ROS/ROS2

Profiling tools

HW/SW co-design

Job description

As the world’s leading accelerated computing company, we are paving the way with innovations in self-driving cars, robotics, machine learning, supercomputing, and visualization. We are building a team that will truly change the world and would love for you to join us. We are seeking a Senior Applied Research Engineer, Accelerator Algorithms to drive applied research and architecture for algorithms on NVIDIA’s Programmable Vision Accelerator (PVA), a power‑efficient, deterministic VLIW/SIMD processor used across NVIDIA DRIVE, Jetson, and IGX platforms.

In this role, you will analyze real‑world AV and physical AI workloads across multimodal sensor processing, perception pipelines, sensor fusion, and real‑time control loops, identify workloads well suited for the PVA and translate them into optimized algorithms.

What You Will Be Doing:

• Research and characterize real-world AV and physical AI workloads to identify algorithms that map well to PVA.
• Develop and optimize PVA algorithms using instruction‑level parallelism, memory‑aware scheduling, efficient data movement and vectorized execution.
• Translate workload and algorithm insights into requirements for PVA hardware architecture, compilers, SDKs, profiling tools, and systems software.
• Build prototypes, benchmarks, and performance models to evaluate PVA algorithm performance across current and future hardware architectures.
• Leverage modern AI‑assisted development tools and agentic workflows to accelerate workload analysis, algorithm creation, benchmarking, and performance exploration.
• Partner with internal teams and customers to understand their systems and production workloads, and drive integration of PVA‑accelerated algorithms into final products to deliver real‑world performance, power, and latency benefits.
• Publish, present, and communicate technical findings across research and engineering teams where appropriate.

What We Need To See:

• BS/MS or PhD in Computer Science, Electrical Engineering, Computer Engineering, Robotics, or a related field, or equivalent experience.
• 12+ years of experience in applied research, programmable accelerator algorithm design, computer architecture, or high‑performance computing.
• Experience with DSP, SIMD, VLIW, fixed‑point arithmetic, memory hierarchy, and low‑level performance optimization.
• Experience with HW/SW co‑design, workload characterization, performance modeling, benchmarking, and bottleneck analysis.
• Familiarity with emerging physical AI workloads such as VLA models, multimodal perception, sensor processing, autonomous systems, or robotics systems.
• Strong programming skills in C++, Python, CUDA, or similar environments.
• Excellent communication skills and the ability to explain complex technical tradeoffs clearly.
• Strong ownership, technical judgment, and ability to operate in ambiguous problem spaces.

Ways To Stand Out From The Crowd:

• Hands‑on experience with CUDA, ROS/ROS2, AV or robotics middleware, sensor processing frameworks, profiling tools, and heterogeneous compute pipelines.
• Strong research track record in computer architecture, autonomous systems or sensor processing.
• Familiarity with safety‑conscious development processes such as ISO 26262, IEC 61508, or similar standards.