Education Requirements:

• Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related field.

Experience Requirements:

• Minimum of 5 years in software architecture, with a focus on runtime systems and hardware-software integration.

Other Requirements:

• Extensive experience with runtime systems and ML runtime frameworks, such as ONNX Runtime, TensorFlow Serving, TorchServe, Apache TVM, VLLM, TRT-LLM, and Glow, and a deep understanding of different types of hardware components such as DSPs, hardware accelerators, ARM cores, and DLAs.

• Strong ability to analyze and compare complex frameworks to inform architectural decisions.

• Excellent verbal and written communication skills, with the ability to convey complex technical concepts to diverse stakeholders.

• Familiarity with the competitive landscape in runtime frameworks and hardware acceleration technologies.

• Experience in leading projects from conception through implementation, with a track record of successful delivery.

• Commitment to staying updated with the latest advancements in runtime systems and hardware integration.

Responsibilities:

• Framework Analysis: Conduct comprehensive evaluations of existing runtime systems and ML runtime frameworks, such as ONNX Runtime, TensorFlow Serving, TorchServe, Apache TVM, VLLM, TRT-LLM, and Glow, to identify their strengths, weaknesses, and applicability to our objectives.

• Architecture Design: Develop a robust runtime framework optimized for Neureality servers, ensuring seamless integration with hardware components such as DSPs, video & audio decoders, ARM cores, and DLAs.

• Hardware Integration: Collaborate with hardware engineers to adapt and optimize software components, maximizing performance and efficiency across various hardware modules.

• Performance Optimization: Implement strategies to enhance system performance, including reducing latency, increasing throughput, and improving resource utilization.

• Cross-Functional Collaboration: Work closely with cross-functional teams to align software architecture with business goals and technological advancements.

Experience Requirements:

• 4+ years of programming languages such as Python (preferably)

• Experience with big data technologies (e.g., Spark, Kafka), cloud platforms (e.g., AWS, Azure), and containerized environments (Docker, Kubernetes)

• Solid understanding of data warehousing, ETL processes, and data pipeline design

Responsibilities:

• Design, implement, and optimize scalable data pipelines and architectures for large-scale data processing

• Ensure data quality, integrity, and availability by establishing best practices and monitoring systems

• Troubleshoot and resolve data-related issues to ensure continuous improvement

• Drive innovation by evaluating new data technologies and tools to improve data engineering practices