LG Electronics
AI Researcher (Efficient AI)
Santa Clara, CA · Full-time · Posted Jul 24, 2026
- Experience
- Relevant post-graduate research and/or industry experience is preferred but not required; no specific number of years stated.
- Education
- M.S. or Ph.D. in Computer Science, Computer Engineering, Machine Learning, Mathematics, or a related technical field.
About the job
Researches and implements methods to make LLMs, VLMs, multimodal models, and AI agents more efficient and deployable, particularly on constrained and on-device systems.
What you'll do
- Research, prototype, and evaluate methods for model compression, efficient inference, and deployment on constrained devices.
- Optimize models and agentic workloads, including long-context inference, KV cache compression, and emerging architectures.
- Build benchmark and experimental pipelines and contribute to publications, technical reports, open-source releases, and intellectual property.
What they ask for
- M.S. or Ph.D. in Computer Science, Computer Engineering, Machine Learning, Mathematics, or a related technical field.
- Research or engineering experience in ML, efficient AI, model optimization, or AI systems.
- Strong programming ability in Python and experience with PyTorch or a comparable deep learning framework.
- Hands-on experience with modern LLMs, SLMs, VLMs, multimodal models, or generative AI systems.
Nice to have
- Publications in reputable ML or systems venues.
- Experience with inference and deployment frameworks, efficiency-aware post-training or fine-tuning, low-level kernels, on-device acceleration, or emerging architectures.
Pay
$84.13 — $91.34 USD (recruiting range; pay basis not stated)
Tools
Python, PyTorch, llama.cpp, GGUF, vLLM, SGLang, TensorRT-LLM
AI focus
Efficient AI research and implementation, including model compression and quantization, inference optimization, reasoning optimization, efficient architectures, and on-device deployment.
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