Top Deep Learning Jobs in Chicago, IL

As a Staff AI Scientist, you will lead AI projects, design deep learning models using multimodal data, and ensure regulatory compliance in healthcare AI products.

Summer quantitative trading intern supporting commodities and capital markets through quantitative research and production-grade predictive models. The role develops deep learning, neural network, and large language model applications in PyTorch using large datasets to support trading strategies involving futures, options, and structured products. Responsibilities include model development, quantitative investment strategy support, stakeholder presentations, and collaboration with a lead strategist in an in-person trading environment.

Design, optimize, and deploy deep learning models for customer behavior prediction. Perform feature engineering, implement research-informed architectures, scale training pipelines, collaborate with client teams, document findings, and uphold engineering best practices.

Lead design and training of large-scale transformer and hybrid foundation models across text and multimodal domains. Own architecture choices, diagnose large-scale training instabilities, optimize scaling tradeoffs (data, compute, model), design loss and alignment strategies, and execute distributed training (FSDP/ZeRO, tensor/pipeline parallelism) with mixed precision to build in-house foundation model expertise.

Lead and grow an engineering team building GPU‑accelerated deep learning inference frameworks. Drive roadmap, collaborate with compiler/libraries/research teams, optimize LLM and multimodal model performance, and oversee multi‑GPU communications and production deployment of inference software.

Design and implement novel neural network architectures for YOLO, run large-scale experiments and ablation studies, optimize models for accuracy and efficiency (quantization/pruning/distillation), build training and evaluation pipelines, and collaborate with R&D and engineering to productionize open-source models.

Conduct research and develop algorithms for real-time video processing and deepfake detection, translating machine learning models for production use.

Lead the development of deep learning models for email data, optimize models, design evaluation frameworks, integrate products, and mentor junior researchers.