Lenovo seeks to drive the development, optimization, and large-scale deployment of cutting-edge AI capabilities across its devices and platforms, ensuring they run seamlessly across a range of computing environments and hardware architectures.
Requirements
- Experience: 10+ years in production software development, including AI/ML engineering, with 5+ years in leadership roles. Proven track record in model deployment, optimization, and benchmarking at scale. Demonstrated ability to deliver production-grade AI models optimized for both on-device and cloud environments.
- Optimization Techniques: Strong expertise in quantization, pruning, distillation, graph optimization (ONNX, TensorRT), mixed precision, and hardware-specific tuning (GPUs, TPUs, custom accelerators).
- Inference Systems: Experience with low-latency serving, batching strategies, caching, and dynamic scaling across clusters.
- Cloud Edge Deployment: Deep knowledge of end-to-end deployment of ML/LLM models. Proven ability to deliver across environments — cloud (AWS/GCP/Azure), hybrid, and edge devices.
- Tooling Frameworks: Familiarity with PyTorch, TensorFlow, JAX, ONNX Runtime, TensorRT, TVM, and model compilation stacks.
- Data Telemetry: Building feedback loops from runtime telemetry to guide retraining, routing, and optimization.
- Excellent leadership, communication, and cross-functional collaboration skills.
Responsibilities
- Lead and scale Lenovo’s AI model deployment and optimization strategy across devices, laptops, and cloud environments.
- Adapt, fine-tune, and optimize open-source foundation models (e.g., OpenAI, Google Gemma) for Lenovo’s product portfolio.
- Drive initiatives in model compression, quantization, pruning, and distillation to achieve maximum efficiency on constrained devices while preserving model quality.
- Oversee performance evaluation, benchmarking, and iterative improvement cycles for large language models, vision models, and multimodal AI.
- Collaborate closely with hardware architecture teams to align AI model efficiency with device and accelerator capabilities.
- Develop hardware-aware optimization algorithms and integrate them into model deployment pipelines.
- Partner with global engineering, research, and product teams to bring optimized AI-powered features (e.g., “Catch Me Up”) to market.
Other
- Establish and maintain reproducible workflows, automation pipelines, and release-readiness criteria for AI models.
- Represent Lenovo in AI model optimization research communities, technical working groups, and industry consortiums.
- Build, mentor, and inspire a high-performance applied AI engineering team.
- Graduate degree (MS or PhD) in Computer Science, AI/ML, Computational Engineering, or related field.
- Experience delivering AI features in consumer electronics or embedded platforms.
