Senior Deep Learning Compiler Engineer - XLA

Jobgether

6d • $152,000 - $241,500 • Remote

About The Position

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Deep Learning Compiler Engineer - XLA in United States.
This role focuses on developing and optimizing compilers for high-performance deep learning workloads on modern GPU architectures. You will design, implement, and tune advanced compiler optimization algorithms to accelerate training and inference for deep learning frameworks at scale. The position involves collaborating with framework teams, hardware engineers, and cross-functional partners to deliver production-grade software that powers next-generation AI systems. You will work on graph partitioning, tensor sharding, performance analysis, and code generation, while also contributing to user-facing library features. This role combines deep technical expertise, creativity, and autonomy in a dynamic, research-driven environment with significant impact on AI computing performance.

Requirements

• Bachelor’s, Master’s, or Ph.D. in Computer Science, Computer Engineering, or related field, or equivalent experience
• 4+ years of experience in performance analysis, compiler optimization, or deep learning software development
• Strong C/C++ programming skills with expertise in software design, debugging, and testing
• Knowledge of CPU, GPU, or other high-performance hardware architectures, including distributed computing
• Experience with CUDA or OpenCL is desirable
• Familiarity with XLA, TVM, MLIR, LLVM, OpenAI Triton, or deep learning frameworks such as JAX, PyTorch, or TensorFlow is a strong plus
• Ability to work independently, define project scope, and deliver high-quality software
• Excellent communication and collaboration skills; experience mentoring junior engineers is a bonus

Responsibilities

• Develop compiler optimization techniques for deep learning network graphs
• Design and implement graph partitioning and tensor sharding for distributed training and inference
• Optimize performance and analyze computational efficiency on GPU hardware
• Generate code for NVIDIA GPU backends using MLIR, LLVM, OpenAI Triton, or similar compilers
• Contribute to user-facing features in deep learning frameworks and related libraries
• Collaborate with GPU hardware teams to align software features with next-generation architectures
• Mentor junior engineers and support knowledge sharing within the team

Benefits

• Competitive salary range ($152,000—$241,500 USD)
• Eligibility for equity, bonuses, and comprehensive benefits packages
• Remote work eligibility with flexibility depending on location
• Opportunities for professional growth, mentorship, and career development
• Dynamic, research-driven environment working on cutting-edge AI technology
• Inclusive, diverse, and collaborative workplace culture

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree