Principal AI Research Engineer

Familiarity with good SW practices and development, including code quality, version control, etc.

Very strong with ML frameworks such as Pytorch, or Tensorflow

Good understanding of Transformer architectures, attention mechanisms, multi-modal foundation models, diffusion policies, fine-tuning, model distillation, mixture of experts, and other similar topics.

Is up to date with research literature and recent ML techniques and methodologies.

Experience developing production AI models is a plus.

Reasonable accommodations will be determined on a case-by-case basis.

As a Principal AI and ML fundamentalist who is an expert at developing cutting-edge AI solutions to complex problems, you will develop code that eventually integrates into production and be responsible for:

Design, implement, and evaluate novel machine learning and deep learning algorithms.

Iterate on AI model development; starting from the data needed for training, architecture, input/output representations, evaluation, and deployment.

Conduct experiments to benchmark new techniques and evaluate model behavior.

Develop tools and frameworks to support scalable and reproducible research and development.

Communicate research findings to leadership in a concise, and convincing manner.