AI Compiler Engineer

About the role

EnCharge AI is looking for an experienced AI Compiler Engineer to lead the development and optimization of graph compilers for cutting‑edge AI and ML workloads. You will work closely with hardware architects, AI researchers, and software teams to maximize performance on EnCharge’s inference accelerators.

Key responsibilities

• Architect, design, and implement compiler optimizations that improve AI model execution, reduce latency, and increase hardware utilization.
• Collaborate with ML researchers, hardware engineers, and software developers to address hardware‑specific challenges and deploy models efficiently.
• Develop graph‑level transformations such as layer fusion, operator fusion, and quantization.
• Create parsing, semantic analysis, and IR generation pipelines for frameworks like TensorFlow and PyTorch.
• Research and integrate the latest advances in compiler design, ML model optimization, and hardware acceleration.
• Provide technical leadership, mentorship, and guidance to a team of engineers focused on compiler improvements.

Required profile

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field (Ph.D. preferred).
• 3+ years of experience in compiler development with a focus on AI/ML graph compilers.
• Proven track record of leading and mentoring engineering teams to deliver successful projects.

Required skills

• Proficiency with AI graph compiler frameworks such as MLIR and Torch‑FX.
• Strong knowledge of hardware architectures (GPUs, TPUs, ASICs) and optimization techniques like fusion, quantization, and tiling.
• Experience with intermediate representations, code parsing, and semantic analysis.
• Programming expertise in C++ and Python.