Job Description
MediaTek Incorporated is a global fabless semiconductor company that enables nearly 2 billion connected devices a year. We are a market leader in developing innovative systems-on-chip (SoC) for mobile device, home entertainment, connectivity and IoT products. MediaTek is the number one Wi-Fi supplier across broadband, retail routers, consumer electronics devices and gaming, and its Wi-Fi 6 chipsets are powering the latest networking equipment for faster computing experiences. MediaTek’s Automotive Platform Business Unit is Hiring a Principal Engineer – Generative AI & Edge Systems, Automotive. In this role, you will: (1) Research and develop Generative AI and deep learning-based systems for in-vehicle domains — Infotainment, Speech, UI, and multimodal ADAS — with a focus on architectures deployable on resource-constrained edge hardware. (2) Lead integration of GenAI frameworks and toolchains optimized for automotive edge compute, driving adoption of cutting-edge on-device AI techniques from research into production. (3) Partner with Silicon and Software engineering teams at HQ (Taiwan) and automotive customers to define and deliver technical solutions for GenAI and LLM requirements, with edge feasibility as a core design constraint from the start. (4) Own end-to-end LLM optimization for on-device deployment on GPUs and NPUs — profiling models, identifying bottlenecks, and driving improvements at both the model level (quantization, distillation, pruning) and framework level to maximize inference performance within embedded compute and power budgets. (5) Track industry and academic advances in edge AI and efficient LLM techniques, translating relevant breakthroughs into practical, deployable improvements for in-vehicle systems.
Main Requirements and Qualifications
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- Master's degree in Computer Science, Electrical Engineering, Mathematics, or related field, with 10+ years of overall software engineering experience, including 4+ years directly relevant to GenAI/LLM systems.
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- Deep hands-on experience with ML/DL frameworks and tooling: TensorFlow, PyTorch, NeMo, TAO, TensorRT, CUDA, and vLLM, with working knowledge of edge-inference frameworks (e.g., TensorRT-LLM, ONNX Runtime, GGUF/llama.cpp).
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- Proven experience optimizing state-of-the-art models for edge deployment — quantization, pruning, distillation — with practical tradeoff analysis across latency, memory bandwidth, and CPU vs. NPU vs. GPU compute.
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- Hands-on experience deploying and optimizing multiple LLMs and multimodal models concurrently on edge devices — managing shared compute/memory budgets, model orchestration, and runtime tradeoffs when running several models side-by-side on constrained hardware.
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- Practical experience with speech and multimodal AI pipelines — ASR, TTS, speech-to-intent, or vision-language fusion — in resource-constrained, real-time environments.
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- Strong programming proficiency in C, C++, and Python, including performance-critical and memory-constrained code.
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- Hands-on experience with embedded software, RTOS, and microcontroller-based platforms.
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- Familiarity with training data preparation, curation, and open-source datasets for fine-tuning or evaluation.
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- Working knowledge of in-vehicle AI technical stacks — Speech, Voice, or ADAS/AD systems.
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- Exposure to automotive functional safety (ISO 26262) and cybersecurity (ISO 21434) standards.
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- Demonstrated ability to move quickly in agile environments, translating research and prototypes into shippable, production-grade systems.
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Salary range: $171,200 - $286,600 annually.
Employee may be eligible for performance bonus, short and long term incentive programs. Actual total compensation will be dependent upon the individual's skills, experience and qualifications. In addition, MediaTek provides a variety of benefits including comprehensive health insurance coverage, life and disability insurance, savings plan, Company paid holidays, Paid time off (PTO), Parental leave, 401K and more.
MediaTek is an Equal Opportunity Employer that is committed to inclusion and diversity to all, regardless of age, ancestry, color, disability (mental and physical), exercising the right to family care and medical leave, gender, gender expression, gender identity, genetic information, marital status, medical condition, military or veteran status, national origin, political affiliation, race, religious creed, sex (includes pregnancy, childbirth, breastfeeding and related medical conditions), and sexual orientation.