Requirements

• A self-starter with a strong passion for excellence. You always want to go above and beyond in everything you do;
• An entrepreneurial “can-do” attitude and an innovative mindset;
• Savvy and professional, ethical, and well developed interpersonal skills;
• Preferably holding a Masters by Research, PhD or Postdoc in computer science (includes AI and Data Science), mathematics, physics, or engineering;
• Sound in the mathematical foundations of ML/AI coupled with practical skills in these fields;
• Good hands-on skills in statistical modeling and data analysis (pandas, Dask, Spark, etc.);
• Experience with multiple ML/DL frameworks (scikit-learn, Dask, Spark Mllib/ML, XGBoost, LightGBM, TensorFlow, Torch, etc.). We expect you to know when and how best to employ them and understand various trade-offs.;
• Understanding of performance issues such as scalability, complexity, and memory footprint of various algorithms;
• Sound problem solving skills and algorithmic approach;
• Expert understanding in at least one specialisation area within ML/AI:
• Modern NLP/NLU using DL frameworks;
• Scaling supervised and unsupervised ML algorithms to large data;
• Bayesian Optimisation (for hyperparameter search and model selection);
• PU Learning;
• Active Learning;
• Time-series analysis including classification, forecasting, and survival analysis;
• GPU acceleration for ML/DL;
• Explainable AI;
• Applications of graphical models in AI such as Bayesian networks, Markov random fields, etc.
• Demonstrated ability to write code that can run in production, in at least one of the following languages: Python, R, Scala, Julia, Java, C++, or Go.