Bachelor or Master of Science degree from an accredited course of study, in AI/ML Engineering, Computer Engineering, Software Engineering, Computer Science, Mathematics, Physics or other technical degree
0-5 years of experience in developing models and ensembles in the AI/ML space
Experience with software architectures and software implementations
Experience with AI/ML technologies, frameworks, models and ensembles
Experience with Pytorch, SciKit Learn, Tensorflow, and similar backend frameworks
Experience with Classification Supervised and Unsupervised models
Experience with Decision Making models, such as Reinforcement learning
Experience with Prediction models, including time series models, regressors
Experience with GenAI models, including LLMs
Experience with Python
Ability to quickly learn new next-generation algorithms and models, including Neurosymbolic reasoning models, and Liquid time-constant models (LTCs)
A strong, influential, innovative, and collaborative engineer that can work in a global team
Strong background with optimizing and validating models
Experience with V&V test benches
Familiarity with Explainable AI (XAI) techniques
Familiarity with ONNX (Open Neural Net Exchange)
Proactively and quickly makes sense of complex issues; responds effectively to complex and ambiguous situations; communicates complicated information simply
Gains others' trust by demonstrating openness and honesty, behaving consistently, and acting in accordance with moral, ethical, professional, and organizational guidelines