AI Compiler Engineer
$190k - $255k • Remote • Remote-US, Canada, Germany and Norway • Full-time
Posted 4mo ago
This job has been open for more than 60 days. It may no longer be actively hiring, so check with the company before putting a lot into an application.
Job Location
Remote-US, Canada, Germany and Norway
Tech Stack
Remote Work Policy
Fully remote
Employment Type
Full-time
Categories
LLM Engineer
About the job
EnCharge AI is seeking a highly skilled and experienced AI Compiler Engineer to spearhead the development and optimization of graph compilers tailored for cutting-edge AI and ML workloads. This role involves collaborating with hardware architects and AI researchers to enhance performance, optimize computation graphs, and enable efficient model deployment on EnCharge's Inference Accelerators. The ideal candidate will architect, design, and implement optimizations for AI model execution on graph compilers to improve performance, reduce latency, and maximize hardware utilization.
Responsibilities
- Architect, design, and implement optimizations for AI model execution on graph compilers to improve performance, reduce latency, and maximize hardware utilization.
- Collaborate with ML researchers, hardware engineers, and software developers to design and deploy AI models, addressing hardware-specific challenges.
- Optimize neural network models through techniques like layer fusion, operator fusion, and graph-level transformations.
- Develop compiler optimizations and passes to convert high-level AI models (e.g., from TensorFlow, PyTorch) into intermediate representations (IR).
- Implement parsing, semantic analysis, and IR generation for deep learning frameworks.
- Research and integrate advancements in compiler design, ML model optimizations, and hardware acceleration into graph compilers.
- Provide leadership, mentorship, and technical guidance to a team of engineers focused on graph compiler optimizations.
Requirements
- Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field (Ph.D. preferred).
- 3+ years in compiler development, with a strong focus on AI or ML graph compilers.
- Proficiency in AI graph compiler frameworks (e.g., MLIR, Torch-FX).
- Solid background in hardware architectures (e.g., GPUs, TPUs, ASICs) and optimization techniques such as fusion, quantization, and tiling.
- Familiarity with neural networks operators and code generation.
- Strong understanding of intermediate representations, code parsing, and semantic analysis in compiler design.
- Proficiency in C++, Python, or other relevant programming languages.
- Open-source contributions to AI software frameworks and libraries are a plus.
- Demonstrated experience leading and mentoring engineering teams with successful project delivery.