Basic Qualifications (Required Skills/Experience):
- 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)
Preferred Qualifications (Desired Skills/Experience):
- Experience with ML Ops and Data Ops
- 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