LLM Algorithmic Optimization Engineer

1600 NIO USA, Inc.; San Jose (CA); On-site; USD 143,200 - 186,000; Full time

Benefits offered by this job

Medical plans

401(k) with brokerage link option

Free lunch and snacks

Onsite gym

Job summary

1600 NIO USA, Inc. in San Jose, California is looking for an expert to optimize large language models and multimodal systems. You will collaborate with teams to integrate models into automotive applications, ensuring efficient deployment.

Ideal candidates have a PhD or Master’s in relevant fields, strong GPU/NPU knowledge, and programming skills in Python and C/C++. Benefits include medical plans, flexible spending accounts, and on-site gym access.

Qualifications

• Currently pursuing or completed a PhD or Master’s degree in a relevant field.
• Strong understanding of optimization techniques for GPU/NPU.
• Familiarity with NLP / Audio / CV algorithms.

Responsibilities

• Optimize large language models and multimodal models.
• Collaborate with cross-functional teams for model integration.
• Contribute to the pipeline from development to deployment.

Skills

GPU/NPU architecture understanding

Proficient in Python

C/C++ programming

Experience with PyTorch

Debugging in distributed environments

Education

PhD or Master’s in Computer Science or related field

Tools

ONNX

AI-related training tools

Job description

About NIO

About NIO NIO is a pioneer and a leading company in the premium smart electric vehicle market. Founded in November 2014, NIO’s mission is to shape a joyful lifestyle. NIO aims to build a community starting with smart electric vehicles to share joy and grow together with users. NIO designs, develops, jointly manufactures and sells premium smart electric vehicles, driving innovations in next‑generation technologies in autonomous driving, digital technologies, electric powertrains and batteries. NIO differentiates itself through its continuous technological breakthroughs and innovations, such as its industry‑leading battery swapping technologies, Battery as a Service (BaaS), as well as its proprietary autonomous driving technologies and Autonomous Driving as a Service (ADaaS). NIO’s product portfolio includes the ES8, ES7/EL7, ES6, EC7, EC6, ET7, and ET5.

Roles and Responsibilities

Conduct research and apply cutting‑edge technologies to optimize large language models (LLMs) and multimodal models, exploring and implementing core algorithmic optimization on heterogeneous architectures for efficient LLM inference as well as deployment across distributed and heterogeneous hardware environments. Focus on model optimization from a systems perspective, ensuring efficient deployment in the vehicle’s digital cockpit and advanced driving (AD) domain. Collaborate with cross‑functional teams to ensure the integration of optimized models into real‑world automotive applications. Contribute to the entire pipeline from research, development, and testing, through to deployment on hardware, including GPUs and other distributed systems.

Qualifications

Currently pursuing or completed a PhD or Master’s degree in Computer Science, Computer Engineering, Applied Mathematics, Communications, Electronics, or a related field with relevant research projects and publications. Strong understanding of GPU/NPU architecture and optimization techniques to identify and address bottlenecks. Proficient in LLM and VLM architectures and algorithms, familiar with transformer‑based NLP / Audio / CV algorithms and technologies. Proficiency in Python and experience with AI‑related training and inference tools such as PyTorch. Proficiency in C/C++ programming, familiar with at least one commonly used LLM inference engine. Hands‑on experience with model‑serving frameworks such as ONNX. Familiarity with debugging code in distributed computing environments. Experience in LLM inference optimization on resource‑constrained edge devices is a plus.

Preferred Qualifications

Ph.D. in computer science, artificial intelligence, or related fields; or Master’s degree plus 3 years of relevant industry experience. Experience in inference optimization techniques of deep learning models or libraries on hardware architectures; familiar with microkernel architecture, Linux kernel, hypervisor, middleware, and application framework. Good publication records and high‑impact innovative papers preferred.

Compensation

The U.S. base salary range for this full‑time position is $143,200.00 – $186,000.00. Pay is determined by location and factors such as skills, experience, and education. This figure represents base salary only and does not include discretionary bonus, equity, or benefits.

Benefits

• Medical plans: CIGNA EPO, HSA, and Kaiser HMO with $0 employee coverage.
• Dental (including orthodontic) and vision plans with $0 employee contribution.
• Company‑paid HSA contribution when enrolled in high‑deductible CIGNA plan.
• Health and dependent care flexible spending accounts (FSAs).
• 401(k) with brokerage link option.
• Company‑paid basic life, AD&D, short‑term and long‑term disability insurance.
• Employee assistance program.
• Sick and vacation time.
• 13 paid holidays per year.
• Paid parental leave (first 8 weeks at full pay, eligible after 90 days).
• Paid disability leave (first 6 weeks at full pay, eligible after 90 days).
• Voluntary benefits: life, AD&D, pet insurance.
• Commuter benefits.
• Mobile cell phone credit.
• Healthjoy mobile benefit app.
• Free lunch and snacks.
• Onsite gym.
• Employee discounts and perks program.