Executive Director - Applied Artificial Intelligence Machine Learning
On-sitePlano, Texas, United States
Job Summary
Develop state-of-the-art machine learning models to solve real-world problems, specifically applying sophisticated methods to natural language processing, speech analytics, time series, and recommendation systems. Collaborate with Business, Technology, Product Management, Legal, Compliance, Strategy, and Business Management teams to deploy solutions into production. Coach other AI/ML team members towards personal and professional success while designing experiments, training frameworks, and evaluating metrics aligned with business goals. Utilize extensive experience with toolkits like TensorFlow and PyTorch to manage big data and scalable model training, effectively communicating technical concepts to both technical and business audiences.
Required Qualifications
- PhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science
- at least 5 years of industry experience
- MS with at least 7 years of industry or research experience in the field
- Solid background in NLP or speech recognition and analytics
- personalization/recommendation
- hands-on experience and solid understanding of machine learning and deep learning methods
- Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)
- Ability to design experiments and training frameworks
- outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals
- Experience with big data and scalable model training
- solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences
- Scientific thinking
- ability to invent
- work both independently
- work in highly collaborative team environments
- Curious
- hardworking and detail-oriented
- motivated by complex analytical problems
Desired Qualifications
- Strong background in Mathematics and Statistics
- familiarity with the financial services industries
- continuous integration models
- unit test development
- Knowledge in search/ranking
- Reinforcement Learning
- Meta Learning
- Experience with A/B experimentation
- data/metric-driven product development
- cloud-native deployment in a large scale distributed environment
- ability to develop and debug production-quality code
- Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journal
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