Li Li Email & Phone Number

Palo Alto, Ca, Us

Foster City, California, United States

Houston, Texas, Us

- Pioneered the launch of HPE’s LLM Online Inference Solution, achieving over $#M in revenue within the first three months. Developed a synergistic go-to-market (GTM) strategy in close collaboration with solution engineering, customer service, and product marketing teams.- Led a team of product managers to build HPE’s LLM Platform from the ground up, including an LLM playground for rapid user experiences, retrieval-augmented generation (RAG) pipelines, LLM evaluation frameworks, deployment, guardrails, drifting detection, and real-time monitoring tools. Defined the product vision, roadmap, team structure, and workstreams to ensure a seamless partnership between product and engineering.- Established scalable product development processes to drive alignment and efficiency, implementing tools like a customer success dashboard, a product intake system, and use case-based prioritization methods. Strengthened collaboration processes between product management and engineering.- Spearheaded a strategic partnership with NVIDIA, integrating NVIDIA AI Enterprise’s NeMo framework (NIMs) with HPE’s AI solutions, culminating in a successful joint product launch. Drove alignment across HPE and NVIDIA teams to ensure seamless software development and rollout.- Fostered cross-functional collaboration by aligning the AI Solutions team with other HPE divisions and creating a virtual joint development team with NVIDIA, ensuring cohesive execution and fostering innovation across the partnership.

San Francisco, California, Us

- Spearhead the development of a machine learning platform / ML accelerator to facilitate deep learning model experimentation and deployment for autonomous vehicles.- Create yearly strategies and defined robust processes, including reviews and checkpoints, in collaboration with key stakeholders in internal model teams and machine learning platform engineer leads, to ensure product delivery and cross-team alignment on roadmaps- Achieve 20x deployment velocity improvement by developing and unifying multiple tools into a single, end-to-end workflow across different compute platforms. - Accomplish highly automated model deployment workflow includes 1) model performance assessment tools; 2) quantization and NAS infrastructure for model selection and optimization; 3) a deep learning compiler that can convert the models running on both GPU and CPU; and 4) disparity debugging tools for debugging. - Drive xfn teams to migrate and bring up machine learning workload to multiple generations of autonomous cars with different compute architectures.

San Francisco, California, Us

- Build an in-house machine learning workflow Orchestration platform and lineage-tracking system.- Drive a data-driven latency testing strategy, develop runtime performance metrics and performance analysis tooling, testing platform with xfn teams (i.e. Simulation, testing, etc) to proactively prevent latency related road events.

San Jose, California, Us

Qeexo develops machine learning and AI solutions on the embedded edge device with the sensor data for industries such as mobile, IoT, and automotive. The solutions have been deployed on over 170 million devices.- Manage and drive machine learning product development life cycle, from defining project objective, acquiring and exploring data, interpreting result, deploying the model, and maintaining the feedback loop to continuous improvement.- Drive and productize the machine learning based proximity sensing software (EarSense), named CES Innovation Awards Honoree & MWC Global Awards Nominee, and deployed in the OPPO Find X.- Define and productize machine learning gesture interaction software (TouchTool) with use cases such as Interactive drawing application in flat panel vendor and the physical dial replacement in the automobile (patent submitted), and Establish strategic partnerships with major Interactive flat panel vendors worldwide and automobile software companies.- Initiate new business model and revenue strategy for machine-learning-based solution (FingerSense) with design and development of a new mini-launcher mobile app (EazLi).

- Launched Internet video discovery and consumption app with machine learning-based content curation based on day-parting algorithms attaining endorsement from Google TV/YouTube and had 10k installations within 2 weeks- Delivered an engaging, immersive video viewing experience on different screens - TV, PC, phone and tablets, with cross-device interaction and user social and engagement tools- Define and develop Matchstick (a streaming dongle), raised half of a million dollars from the sale of 25,000 units in 25 days in Kickstarter

Us

-Defined and delivered TelTel Soft client supporting VoIP, buddy list, presence, and instant messaging, with 2+ million subscribers-Defined OTT box specification of user interface and operation system including provision, configuration, device management features

Chaoyang District, Beijing, Cn

Defined, developed and launched three products: Human Resource (HR) Select Employee Assessment Solution; Career-Oriented Services and Cambridge English: Young Learners online learning platform

Managed project oversight, communication, deliverables, and accountability throughout the full product development life cycle of an online learning experience for a UK-based education program in China.

Master Of Science - Ms, Finance And Management

Bachelor, Economics