Model Optimization Engineer

Job

Location:

Chicago, IL (Hybrid: 3 days on site, 2 days remote)

Posted on:
Sunday, December 21, 2025

We are Lenovo. We do what we say. We own what we do. We WOW our customers. Lenovo is a US $69 billion revenue global technology powerhouse, ranked #196 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world's largest PC company with a full‑stack portfolio of AI‑enabled, AI‑ready, and AI‑optimized devices (PCs, workstations, smartphones, tablets), infrastructure (server, storage, edge, high performance computing and software‑defined infrastructure), software, solutions, and services.

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Lenovo is building Quantum, a next‑generation hybrid AI platform that spans Windows, Android, and cloud. We are hiring for a Model Optimization Engineer to optimize and deploy large models for edge devices. In this role you will master multiple technologies, such as Quantization frameworks (Tensor

RT, ONNX Runtime), edge AI runtimes (Execu Torch, llama.cpp), NPU SDKs (Qualcomm QNN), model compression libraries, profiling tools (NVIDIA Nsight, Snapdragon Profiler).

On‑device AI is the future‑enabling real‑time, private, and always‑available intelligence. You'll push the boundaries of what's possible on mobile hardware, delivering AI experiences that run locally with low latency and all‑day battery life. Your optimizations directly enable breakthrough product features.

Chicago, IL;
Hybrid (3 days on site, 2 days remote)

• Optimization and deployment of large models (LLMs, VLMs, diffusion) for edge devices using quantization (INT4/INT8), pruning, knowledge distillation, and LoRA.
• Partner with silicon teams to optimize model execution on heterogeneous hardware: NPUs (Qualcomm Hexagon, Google Edge TPU), GPUs, and CPUs.
• Implement and benchmark deployment frameworks:
  Tensor
  
  RT‑LLM, ONNX Runtime, Execu Torch, llama.cpp, MLC‑LLM.
• Drive hardware‑software co‑design, influencing sensor and silicon roadmaps to enable efficient AI inference.
• Build ML ops infrastructure: model serving, A/B testing, performance monitoring, continuous optimization.
• Stay at the forefront of on‑device AI: sub‑10B parameter models, mixed precision, sparse attention, federated learning.

• 3+ years in ML engineering or systems, with 3+ years focused on model optimization and deployment.
• Bachelor's degree in Engineering or Computer Science.
• Experience in model compression: quantization (QAT, PTQ), pruning, distillation, low‑rank adaptation.
• Hands‑on experience with mobile/edge AI frameworks (Tensor
  
  RT, ONNX, TFLite, CoreML).
• Experience in C++/Python and performance optimization (CUDA, OpenCL, or NPU programming).
• Experience in shipping ML models to production on resource‑constrained devices.

• Understanding of hardware architectures: NPU/GPU/CPU characteristics, SIMD operations, memory hierarchies.

The base salary budgeted range for this position is $110K–$150K. Individuals may also be considered for bonus and/or commission. Lenovo's various benefits can be found at

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, religion, sexual orientation, gender identity, national origin, status as a veteran, and basis of disability or any federal, state, or local protected class.