GPU Modelling Expert

Experience: 15+ years (Senior / SME level)

Proficiency in C/C++ programming languages

Experience in GPU modeling and simulation

Expertise in Computer Architecture

Knowledge of Graphics/Compute APIs like OpenGL and/or DirectX, OpenCL and/or CUDA, Vulkan

Strong debugging and problem-solving skills

Understanding of GPU architecture and graphics pipeline

Knowledge of software development life cycle and tools

Excellent written and verbal communication skills

Ability to work independently and collaboratively within a team

Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field

Experience in semiconductor design services is a plus

Working independently with little supervision.

Provide some supervision/guidance to others.

Having a moderate amount of influence over key organizational decisions (e.g., is consulted by senior leadership to provide input on key decisions).

Use deductive and inductive problem solving; multiple approaches may be taken/necessary to solve the problem

Must have excellent verbal and written communication skills to convey information to various stakeholders some of whom may have limited knowledge of the subject in question

Building and improving our ecosystem around GPU-accelerated computing including developing large scale automation solutions.

Supporting our researchers to run their flows on our clusters including performance analysis and optimizations of deep learning workflows. Improving reliability and overall Researcher Productivity.

Architect and implement brand new strategies to optimize the utilization of our AI computing clusters, driving operational efficiency and resource maximization.

Pioneer innovative solutions to streamline support processes, enabling our team to manage an unprecedented scale of GPU resources

Lead the charge in building a future-proof AI computing infrastructure, ensuring seamless scalability and resilience to power groundbreaking AI models and applications.

Collaborate with multi-functional teams to identify bottlenecks and opportunities for optimization, continuously improving the performance and cost-effectiveness of our AI computing operations.

Empower your team with the tools, processes, and standard methodologies necessary to thrive in a dynamic, high-intensity environment, fostering a culture of operational excellence and continuous improvement

Desirable Additional Qualifications:

Knowledge of Other Operating Systems: Familiarity with Windows, FreeBSD or RTOS driver models for cross-platform development.

Experience with FPGA, SoC, or Custom Hardware: Useful for teams working on nonstandard PCIe endpoints or accelerators.

Performance Tuning: Skills in profiling and optimizing for low-latency, high-throughput data paths.

Community Engagement: Involvement in Linux kernel mailing lists, conferences (such as Linux Plumbers Conference), or speaking at industry events.

Note: Please send Cv only, who can attend the interview weekdays, with short notice period (max 15 days only)

Job Location:
Bangalore (Work from office)