AI Compiler Engineer
EnCharge AI · United States
- Hybrid
- Full-time
- $220,000 / year
- United States
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Job highlights
- Develop and optimize AI graph compilers.
- Collaborate with hardware and AI teams.
- Improve AI model performance and efficiency.
- Implement compiler passes and IR generation.
- Lead and mentor engineering teams.
About the role
AI Compiler Engineer
EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems.
About the Role
EnCharge AI is seeking a highly skilled and experienced AI Compiler Engineer to spearhead the efforts in developing and optimizing graph compilers tailored to cutting-edge AI and ML workloads. You will collaborate with hardware architects, and AI researchers to enhance performance, optimize computation graphs, and enable efficient model deployment on EnCharge’s Inference Accelerators.
Responsibilities
- Architect, design, and implement optimizations for AI model execution on graph compilers to improve performance, reduce latency, and maximize hardware utilization.
- Work closely with ML researchers, hardware engineers, and software developers to design and deploy AI models, understanding and addressing hardware-specific challenges.
- Work on performance optimizations for neural network models, such as layer fusion, operator fusion, and graph-level transformations.
- Develop compiler optimizations and passes that 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 the latest 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.
Qualifications
- 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 programming languages commonly used in compiler development.
- Open-source contributions to AI software frameworks and libraries is a plus
- Demonstrated experience leading and mentoring engineering teams with successful project delivery.
EnchargeAI is an equal employment opportunity employer in the United States.
The salary range for this position is $190,000 to $255,000 USD per year. Actual compensation offered will be determined based on job-related knowledge, skills, and experience.
Key skills/competency
- AI Compiler Engineer
- Graph Compilers
- ML Workloads
- Performance Optimization
- Hardware Architectures
- TensorFlow
- PyTorch
- MLIR
- C++
- Python
Skills & topics
- AI Compiler Engineer
- Graph Compiler
- MLIR
- Torch-FX
- Compiler Optimization
- AI Hardware
- Machine Learning
- Performance Engineering
- C++
- Python
- Edge Computing
- In-Memory Computing
How to get hired
- Tailor your resume: Highlight compiler development, AI/ML graph compilers, MLIR, and hardware architecture experience.
- Showcase your work: Emphasize experience with TensorFlow, PyTorch, C++, and Python in your application.
- Demonstrate leadership: Detail your experience leading and mentoring engineering teams for successful project delivery.
- Prepare for technical interviews: Be ready to discuss compiler design, AI model optimization, and code generation.
- Highlight open-source contributions: Mention any contributions to AI software frameworks or libraries.
Technical preparation
Master AI graph compiler frameworks like MLIR.,Practice optimizing neural network operators.,Implement compiler passes for IR generation.,Study hardware architectures and optimization techniques.
Behavioral questions
Describe leading an engineering team.,How do you collaborate with researchers?,How do you handle hardware-specific challenges?,Share an experience mentoring engineers.
Frequently asked questions
- What is EnCharge AI's core technology?
- EnCharge AI specializes in advanced AI hardware and software systems, featuring next-generation in-memory computing technology for highly efficient and dense computation, particularly for power-constrained applications.
- What are the primary responsibilities of an AI Compiler Engineer at EnCharge AI?
- The AI Compiler Engineer will architect, design, and implement optimizations for AI model execution on graph compilers, focusing on performance, latency reduction, and hardware utilization. This includes working with ML researchers and hardware engineers, developing compiler passes, and ensuring efficient model deployment on EnCharge's Inference Accelerators.
- What AI graph compiler frameworks are essential for this role?
- Proficiency in AI graph compiler frameworks such as MLIR and Torch-FX is essential for this role. Familiarity with these tools is crucial for developing and optimizing AI model execution.
- What programming languages are commonly used for this AI Compiler Engineer position?
- Proficiency in C++ and Python is commonly required for this role, as these are the primary programming languages used in compiler development and for working with AI/ML frameworks.
- What kind of hardware architectures should I be familiar with for the AI Compiler Engineer role?
- A solid background in hardware architectures like GPUs, TPUs, and ASICs is expected. You should also understand optimization techniques such as fusion, quantization, and tiling relevant to these architectures.
- Does EnCharge AI value open-source contributions for the AI Compiler Engineer role?
- Yes, open-source contributions to AI software frameworks and libraries are considered a plus for the AI Compiler Engineer position, demonstrating engagement with the broader AI development community.
- What is the expected educational background for an AI Compiler Engineer at EnCharge AI?
- A Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field is required. A Ph.D. in a relevant field is preferred for this position.
- How does EnCharge AI approach compensation for the AI Compiler Engineer role?
- The salary range for this position is $190,000 to $255,000 USD per year. Actual compensation will be determined based on factors such as job-related knowledge, skills, and experience.