AI Research Scientist/Engineer Multimodal VLM and MLLM

ethods, technologies, and best practices

• Explore new data sources and discover techniques for best leveraging data

Minimum Qualifications

• A Master's or PhD in a field related to AI/ML, such as: Computer Science, Mathematics, Statistics, Physics, Linguistics, Mechanical Engineering, or related disciplines

• Strong background applying Deep Learning techniques (including implementing custom architectures, optimizing model performance, developing novel loss functions, metrics, and benchmarks, and deploying production-ready solutions)

• Familiarity in statistical methods for Machine Learning (e.g. Bayesian methods, HMMs, graphical models, dimension reduction, clustering, classification, regression techniques, etc.)

• Familiarity with PyTorch, PyTorch Lightning, or similar frameworks

• Strong coding abilities in Python

• Strong Software development skills and familiarity with GPUs, MLOps, Git, High-performance large-scale ML systems and platforms

• Experience with Transformers, LLMs, NLP, Multi-modal Deep Learning, and VLMs/MLLMs

• Publication track record in machine learning conferences and/or journals

Preferred Qualifications

• Significant post-graduate research experience, or five or more years of work experience (actual job title/position will be commensurate with experience)

• Experience with foundation and open-source models, meta/transfer learning, fine-tuning, distillation, multi-task/continual learning, RL, RLxF, and/or image/audio/video/3D generation/understanding

• Experience or familiarity with the 3D Graphics/Animation, Manufacturing, Engineering, Architecture, and/or Construction domain

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