Top Deep Learning Jobs in NYC, NY

Implement deep-learning, computer vision, and inverse-procedural modeling algorithms in Python to convert large 2D/3D and geospatial datasets into high-fidelity 3D content. Apply cutting-edge ML and graphics research, deploy and test code on remote Unix machines, manage code with Git, and collaborate with founding leadership to translate product vision into technical milestones.

Senior ML engineer building and deploying deep learning models (transformers, foundation models, transfer learning) for oncology real-world data. Responsibilities include research and development of predictive models (digital twins, endpoint prediction, trial optimization), extending models across data sources, supporting client engagements, and partnering with product and engineering to productionize reproducible, maintainable solutions while communicating results to technical and non-technical stakeholders.

Lead the integration of advanced imaging analytics and AI into drug development, focusing on medical image analysis using deep learning. Collaborate with clinical teams and develop models for disease detection and treatment response assessment.

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.

Partner with quantitative researchers to design, build, optimize, and scale deep learning models and tooling for research and production. Work includes model architecture, distributed training, inference optimization, ML libraries, and high-performance computing to improve training speed, scalability, reliability, and cost-efficiency in systematic investing workflows.

Design and train physics-informed deep learning models (PINNs, FNOs, Neural Operators) for electromagnetic and heat PDEs; build ECAD-to-tensor/graph data pipelines; calibrate models with lab measurements (VNA, TDR, EMI); integrate multimodal upstream models (GNNs/LLMs); and optimize GPU training/inference for real-time (<100ms) execution.

Lead and scale an engineering team building GPU-accelerated deep learning inference frameworks. Drive strategy and roadmap, partner with compiler/libraries/research teams, oversee performance tuning and multi-GPU optimizations, mentor engineers, and deliver production-ready inference pipelines for LLM, multimodal, and generative AI across datacenter and edge platforms.

Lead research and design of large-scale deep learning systems for protein structure prediction and molecular glue design. Develop novel architectures and training paradigms, collaborate with chemistry/biology experts, publish at top ML venues, and apply models to drive drug discovery value.

The Staff Data Scientist will design and optimize deep learning models for fraud detection, mentor peers, and lead data science initiatives.

The role involves conducting deep learning research, building training pipelines, enhancing frameworks, and collaborating with teams to improve trading strategies.