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Nio

Develops and sells premium smart EVs

AI Technical Lead

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeSan Jose, CA, USA$192.1k - $249.6k

About the Job

Requirements

  • A Ph.D. in Computer Science, Computer Engineering, Artificial Intelligence, or a related field with 8 or more years of relevant industry experience, or a Master’s degree with 12 or more years of relevant industry experience.
  • Proven experience leading technical teams or driving complex architectural roadmaps.
  • Capability to lead full-stack AI systems engineering, with deep hands-on mastery in at least one or two core domains and systemic breadth to lead engineers across the others.
  • Experience designing, scaling, and deploying production-grade distributed machine-learning systems, balancing cloud infrastructure with edge constraints using routing paradigms such as cascading inference architectures and semantic routing.
  • Experience optimizing state-of-the-art large language model and vision-language model inference pipelines.
  • Deep understanding of model compression techniques, including post-training quantization, quantization-aware training, AWQ, FP8, and INT4; hardware-aware compute optimization such as FlashAttention; and memory management such as PagedAttention and KV-cache compression or eviction.
  • Proficiency in C++ and production-grade Python.
  • Deep understanding of edge/cloud model-serving frameworks such as vLLM, TensorRT-LLM, ExecuTorch, and MLC-LLM, and AI compilers such as MLIR, Apache TVM, and Triton for compute-graph optimization and custom kernel development.

Responsibilities

  • Lead the architectural design and strategic vision for hybrid inference systems, dynamically distributing large language model and vision-language model workloads across edge-computing environments and cloud infrastructure.
  • Lead, mentor, and inspire specialized engineers working across distributed-systems orchestration, inference optimization, and AI compiler engineering; drive the technical roadmap, foster innovation, and guide domain experts through complex system tradeoffs.
  • Oversee the architecture of high-availability orchestration engines that intelligently route inference tasks.
  • Guide development of cascading inference mechanisms, dynamic model fallback strategies, and robust telemetry to ensure continuous inference under varying connectivity constraints.

Desired Qualifications

  • Deep understanding of privacy-preserving AI techniques, including federated learning, differential privacy, and secure enclaves, for processing sensitive data across edge and cloud environments.
  • Publications in relevant AI, machine-learning, or systems conferences such as NeurIPS, ICML, or MLSys, or active contributions to open-source machine-learning infrastructure projects such as vLLM, ONNX Runtime, Apache TVM, or llama.cpp.

About the Company

Nio

Develops and sells premium smart EVs

NIO designs, develops, manufactures and sells premium smart electric vehicles and builds a community aroundEV ownership. Its cars are high‑end SUVs and sedans that integrate autonomous driving, digital technologies and advanced electric powertrains. The company differentiates itself with services and technologies such as Battery as a Service (BaaS) and battery swapping stations, as well as proprietary autonomous driving systems and an Autonomous Driving as a Service (ADaaS) offering. NIO’s products work by pairing electric vehicles with a flexible battery service model and software-driven driving features that continuously improve through over‑the‑air updates and on‑vehicle sensors. The company aims to let customers share joy and grow with a user community while advancing next‑generation mobility through its EV lineup and related services.

Company size
5,001-10,000
Company stage
IPO
Headquarters
Huangpu, China
Founded
2014

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