Base Salary
$255k - $351k/yr
Responsibilities
- Lead evaluation, selection, and integration of frontier LLM ecosystems and commercial AI platforms.
- Architect a unified distributed AI platform for data processing, model training, inference pipelines, and evaluation frameworks.
- Embed with autonomous-driving engineering teams to identify bottlenecks and deliver production-ready AI infrastructure, copilots, and developer ecosystems.
- Design scalable LLMOps/MLOps automation for deployment, monitoring, and continuous feedback.
- Optimize GPU cluster utilization, inference latency, throughput, and large-scale production environments.
- Define the technical roadmap for AI infrastructure and connect external innovations with internal systems.
- Write core code, debug deep system issues, and optimize low-level execution paths.
- Influence Algorithms, Infrastructure, and Hardware teams toward adoption of an AI-first engineering paradigm.
Requirements
- Hands-on proficiency in core languages such as C++, Python, Java, and JavaScript.
- Proven experience designing complex system-level architectures while executing hands-on engineering work.
- Experience leading or substantially contributing to large-scale enterprise AI transformation or building enterprise-grade AI/ML platforms from 0 to 1.
- Deep practical experience with distributed LLM training, inference optimization, and large-scale compute cluster infrastructure and operations.
- Hands-on deployment, tuning, and optimization experience with PyTorch, Ray, vLLM, Triton Inference Server, Kubernetes, DeepSpeed, and Megatron-LM.
- Demonstrated ability to align and influence diverse engineering teams without relying on formal administrative authority.
- Preferred: 8–10+ years of engineering experience in systems software, core cloud infrastructure, or production-grade machine learning platforms.
- Preferred: familiarity with autonomous-driving algorithms, robotics, physics-based simulation engines, or ultra-large-scale ML clusters.
- Preferred: experience building AI copilots, autonomous multi-agent frameworks, or developer productivity platforms.
- Preferred: success delivering complex projects in high-pressure or mission-critical environments.
- Preferred: contributions as an open-source maintainer, technical author, or industry conference speaker.
Benefits
- Full-time position with bonus, equity, and benefits in addition to base salary.
- Annual base salary range of $255,000–$351,000, with actual pay determined by location, skills, experience, and education or training.
Tech Stack
Categories
About DiDi
DiDi Global Inc. is a leading mobility technology platform. It offers a wide range of app-based services across Asia Pacific, Latin America, and other global markets, including ride hailing, taxi hailing, designated driving, hitch and other forms of shared mobility as well as certain energy and vehicle services, food delivery, and intra-city freight services. DiDi provides car owners, drivers, and delivery partners with flexible work and income opportunities. It is committed to collaborating with policymakers, the taxi industry, the automobile industry, and the communities to solve the world’s transportation, environmental, and employment challenges through the use of AI technology and localized smart transportation innovations. DiDi strives to create better life experiences and greater social value, by building a safe, inclusive, and sustainable transportation and local services ecosystem for cities of the future.