AI Compiler Engineer

Introduction

This position is for a AI Engineer who is well versed with Compiler skills and strong back end development knowledge in C++. The engineer will get to lead in building AI compilers and low level AI device handling solutions for IBM Z systems.

Your Role And Responsibilities

• Lead Development and deployment of AI Compilers at system level, leveraging deep expertise in AI/ML and Data Science to ensure scalability, reliability, and efficiency.
• Direct the implementation and optimization of AI Device specific compiler technology, personally driving solutions for complex problems.
• Collaborate closely with cross-functional teams hands-on approach to ensure seamless integration and efficiency.
• Proactively stay abreast of the latest advancements in AI/ML technologies and actively contribute to the development and improvement of AI frameworks and libraries, leading by example in fostering innovation.
• Effectively communicate technical concepts to non-technical stakeholders, showcasing excellent communication and interpersonal skills while leading discussions and decision-making processes.
• Uphold industry best practices and standards in AI engineering , maintaining unwavering standards of code quality, performance, and security throughout the development lifecycle.
  
  

• AI compiler development Leadership:
• Deep experience in demonstrating coding skills, teaming capabilities, and end-to-end understanding of Enterprise AI product.
• Deep background in machine learning, deep learning.
• Hands-on expertise with MLIR and other AI compilers like XLA, TVM, etc.
• Deep understanding of AI accelerators like GPU, TPU, Gaudi, Habana, etc.
• Expertise with product design, design principles and integration with various other enterprise products.
• Traditional AI Methodologies Mastery:
• Demonstrated proficiency in traditional AI methodologies, including mastery of machine learning and deep learning frameworks.
• Familiarity with model serving platforms such as Triton inference server, TGIS and vLLM, with a track record of leading teams in effectively deploying models in production environments.
• Proficient in developing optimal data pipeline architectures for AI applications, taking ownership of designing scalable and efficient solutions.
• Development Ownership:
• Proficient in backend C/C++, with hands-on experience integrating AI technology into full-stack projects.
• Demonstrated understanding of the integration of AI tech into complex full-stack applications.
• Strong skills in programing with Python
• Strong system programming skills
• Problem-Solving and Optimization Skills:
• Demonstrated strength in problem-solving and analytical skills, with a track record of optimizing AI algorithms for performance and scalability.
• Leadership in driving continuous improvement initiatives, enhancing the efficiency and effectiveness of AI solutions.
  
  

• Knowledge in AI/ML and Data Science:
• Over 13 years of demonstrated leadership in AI/ML and Data Science, driving the development and deployment of AI models in production environments with a focus on scalability, reliability, and efficiency.
• Ownership mentality, ensuring tasks are driven to completion with precision and attention to detail.
• Compiler design skills:
• Proficiency in LLVM
• Base compiler design concepts
• Commitment to Continuous Learning and Contribution:
• Demonstrated dedication to continuous learning and staying updated with the latest advancements in AI/ML technologies.
• Proven ability to contribute actively to the development and improvement of AI frameworks and libraries.
• Effective Communication and Collaboration:
• Strong communication skills, with the ability to effectively convey technical concepts to non-technical stakeholders.
• Excellence in interpersonal skills, fostering collaboration and teamwork across diverse teams to drive projects to successful completion.