We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1 We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Senior Deep Learning Compiler Engineer
Location
United States
Posted
13 days ago
Salary
Not specified
No structured requirement data.
Job Description
Role Description
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. This role combines deep technical expertise, creativity, and autonomy in a dynamic, research-driven environment with significant impact on AI computing performance.
- 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
Qualifications
- 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
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
Job 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
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
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JobgetherWe use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1 We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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