Director Engineering - Ai Software Stack

• AI/ML Strategy Platform Leadership
• Define and own the AI/ML technology roadmap aligned with business goals across automotive and edge AI platforms.
• Drive adoption of LLMs, VLMs/LVMs, multimodal AI, and agentic AI systems for realworld, safetycritical deployments.
• Influence platform and siliconlevel decisions by translating AI workload requirements into hardware and software capabilities.

Bachelor''s degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience. ORMaster''s degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience. ORPhD in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience. 2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc.

• Oversee endtoend delivery of AI systems from research to production, including model onboarding, optimization, validation, and lifecycle management.
• Ensure performance, power, latency, memory, and accuracy targets are met across heterogeneous compute (CPU/GPU/DSP/NPU).
• Establish best practices for model optimization (quantization, compression, batching, KVcache tuning, mixed precision).

• Build, mentor, and scale multidisciplinary AI/ML engineering teams (ML engineers, systems engineers, platform engineers).
• Set technical direction, define career growth paths, and uphold a high bar for engineering excellence.
• Foster a culture of ownership, accountability, and innovation.

• Bachelors degree in Engineering, Computer Science, or a related field.
• 25+ years of industry experience in software engineering.
• 20+ years of people management experience, including managing managers or senior technical leads and customers.
• Strong background in AI/ML system design, not just model development.
• Handson experience with ML frameworks (PyTorch, TensorFlow, ONNX) and edge/embedded deployment.
• Proven ability to deliver largescale, production AI systems in complex environments

• Masters or PhD in AI/ML, Computer Science, or related field.
• Deep understanding of LLMs, VLMs/LVMs, multimodal and agentic AI architectures.
• Experience with automotive or industrial platforms, embedded Linux/QNX, and realtime constraints.
• Familiarity with QNNlike runtimes, inference SDKs, and heterogeneous acceleration.
• Strong customerfacing experience, including executivelevel technical discussions.
• Track record of influencing product and platform roadmaps through technical leadership.
• Experience in software architecture and design patterns
• Knowledge of architectural approaches for large-scale software applications
• Previous customer-facing experience is advantageous
• Exposure to fine-tuning GenAI models and reinforcement learning considered a plus
• Expertise in inference accuracy, throughput optimization, and edge deployment highly desirable
• Lead system-level problem triage to identify root causes and communicate testing/debugging results to relevant stakeholders