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.
1. 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.
2. Direct the implementation and optimization of AI Device specific compiler technology, personally driving solutions for complex problems.
3. Collaborate closely with cross-functional teams hands-on approach to ensure seamless integration and efficiency.
4. 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.
5. Effectively communicate technical concepts to non-technical stakeholders, showcasing excellent communication and interpersonal skills while leading discussions and decision-making processes.
6. Uphold industry best practices and standards in AI engineering , maintaining unwavering standards of code quality, performance, and security throughout the development lifecycle.
1. 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.
2. 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.
3. 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
4. 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.
1. 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.
2. Compiler design skills:
- Proficiency in LLVM
- Base compiler design concepts
3. 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.
4. 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.