Development Engineer

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We are seeking an experienced Compiler Engineer to join our GPU Assembler Team, working on tools that power high-performance applications across HPC, Deep Learning, and Autonomous Driving domains. In this role, you will contribute to building industry-leading Assembler, Disassembler, and Code Analysis Tools that help developers worldwide achieve maximum performance and efficiency on current and next-generation GPUs.

You will be part of a core engineering team responsible for essential platform components enabling general-purpose GPU computation. The team's tools—widely used across the globe—provide binary analysis, code optimization insights, and high-performance assembly capabilities for critical workloads.

Responsibilities:

Lead the design and development of the client’s GPU Assembler and Disassembler.

Implement advanced binary analysis and instrumentation features (e.g., call-graph generation, register usage analysis, binary patching).

Collaborate with GPU architecture, debugger, and profiler teams to understand requirements and deliver new enhancements.

Ensure compatibility, reliability, and high-quality code generation by working closely with related component development teams.

Engage with customers and partners to gather feedback and drive innovative features into the product roadmap.

Required Qualifications:

BS/MS in Computer Science, Computer Engineering, or related field.

5+ years of experience in low-level system software development, with 3+ years focused on assemblers, binary analysis tools, or debuggers.

Strong analytical skills and proficiency in C/C++ programming.

Experience in at least one area of compiler development: feature support, code generation, or compiler infrastructure.

Understanding of assembly languages and processor ISAs (GPU ISA is a plus).

Knowledge of object file formats (ELF) and debugging formats (DWARF).

Preferred Qualifications:

Understanding of debugger/profiler tools, binary tools, linker internals, and experience with binary analysis or instrumentation tools (e.g., BOLT).

Familiarity with AI-assisted development tools (e.g., Cursor, Windsurf).

Knowledge of GPU programming and compute APIs such as CUDA or OpenCL.