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NIO USA INC
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  • AI Technical Lead  

    - San Jose
    Job DescriptionJob DescriptionAbout NIONIO Inc. is a pioneer and a lea... Read More
    Job DescriptionJob Description

    About NIO

    NIO Inc. is a pioneer and a leading company in the global smart electric vehicle market. Founded in November 2014, NIO aspires to shape a sustainable and brighter future with the mission of “Blue Sky Coming”.

    NIO envisions itself as a user enterprise where innovative technology meets experience excellence. NIO designs, develops, manufactures and sells smart electric vehicles, driving innovations in next-generation core technologies. NIO distinguishes itself through continuous technological breakthroughs and innovations, exceptional products and services, and a community for shared growth.

    NIO provides premium smart electric vehicles under the NIO brand, premium smart electric vehicles for families through the ONVO brand, and small smart high-end electric cars with the FIREFLY brand.

    ResponsibilitiesArchitect the Hybrid AI Vision: Lead the architectural design and strategic vision for hybrid inference systems, dynamically distributing Large Language Model (LLM) and Vision-Language Model (VLM) workloads across edge computing environments and cloud infrastructure.Team Leadership & Innovation: Lead, mentor, and inspire a team of specialized engineers working across distributed systems orchestration, inference optimization, and AI compiler engineering. While you are not expected to be a hands-on master of every domain, you will drive the overarching technical roadmap, foster a culture of cutting-edge innovation, and guide domain experts in navigating complex system tradeoffs.Design Dynamic Orchestration & Resilience: Oversee the architecture of high-availability orchestration engines that intelligently route inference tasks. Guide the team in developing cascading inference mechanisms, dynamic model fallback strategies, and robust telemetry to ensure continuous, steady-state inference under varying connectivity constraints.QualificationsEducation & Experience: Ph.D. in Computer Science, Computer Engineering, Artificial Intelligence, or a related field with 8+ years of relevant industry experience (or Master’s degree with 12+ years), including proven experience leading technical teams or driving complex architectural roadmaps.End-to-End Systems Leadership (T-Shaped Profile): Demonstrated capability to lead full-stack AI systems engineering. You possess deep, hands-on mastery in at least one or two of the following core domains, coupled with the comprehensive systemic breadth required to effectively lead engineers working across the others:Distributed Systems & Hybrid Inference: Designing, scaling, and deploying production-grade distributed ML systems. Balancing cloud infrastructure with edge constraints using modern routing paradigms, such as cascading inference architectures and semantic routing.Algorithmic & Inference Optimization: Proven experience optimizing state-of-the-art LLM/VLM inference pipelines. Deep understanding of model compression (e.g., PTQ, QAT, AWQ, FP8/INT4), hardware-aware compute optimizations (e.g., FlashAttention), and advanced memory management (e.g., PagedAttention, KV cache compression/eviction).Advanced Systems & Compiler Engineering: C++ and production-grade Python proficiency. Deep understanding of edge/cloud model-serving frameworks (e.g., vLLM, TensorRT-LLM, ExecuTorch, MLC-LLM) and AI compilers (e.g., MLIR, Apache TVM, Triton) for compute graph optimization and custom kernel development.

    Preferred Qualifications

    Privacy & Security: Deep understanding of privacy-preserving AI techniques (federated learning, differential privacy, secure enclaves) essential for processing sensitive data across edge and cloud environments.Community Engagement & Open Source: Publications in relevant AI, ML, or systems conferences (e.g., NeurIPS, ICML, MLSys), or active contributions to open-source ML infrastructure projects (e.g., vLLM, ONNX Runtime, Apache TVM, llama.cpp).Benefits

    Along with competitive pay, as a full-time NIO employee, you are eligible for the following benefits on the first day you join NIO:

    Anthem Blue Cross, HSA, and Kaiser HMO medical plans with $0 for Employee Only Coverage.  Dental (including orthodontic coverage) and vision plan.  Both provide options with a $0 paycheck contribution covering you and your eligible dependents.Company Paid HSA (Health Savings Account) Contribution when enrolled in the High Deductible Anthem Blue Cross medical planHealthcare and Dependent Care Flexible Spending Accounts (FSA)401(k) with Brokerage Link optionCompany paid Basic Life, AD&D, short-term and long-term disability insuranceEmployee Assistance ProgramSick and Vacation time13 Paid Holidays a yearPaid Parental Leave for first 8 weeks at full pay (eligible after 90 days of employment with NIO)Paid Disability Leave for first 6 weeks at full pay (eligible after 90 days of employment with NIO)Voluntary benefits including: Voluntary Life and AD&D options for you, your spouse/domestic partner and dependent child(ren), pet insuranceCommuter benefitsMobile Cell Phone CreditFree lunch and snacksOnsite gymEmployee discounts and perks programCompensationThe US base salary range for this full-time position is $192,100.00 - $249,600.00.

    Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.

    Please note that the compensation details listed in US role postings reflect the base salary only. It does not include discretionary bonus, equity, or benefits.

    We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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