Design, develop, deploy and improve production-grade near realtime scalable machine learning and statistical predictive models and NLP from near realtime call transcripts and utterances
Develop novel algorithms and models using state-of-the-art techniques like deep learning neural networks (auto-encoders, feedforward networks, RNNs/CNNs, etc.) and NLP model architectures and algorithms such as BERT (and derivatives like BioBERT, RoBERTa, ALBERT etc.), BiLSTM, XLNet, T5, ELECTRA, PaLM and more
Partner with cross-functional teams, understand problems, and identify opportunities where advanced analytics and machine learning techniques can be used to make a significant impact and then design, develop, deploy and monitor those ML solutions Deployment.
Capture and inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).
Design, implement, deploy, and maintain deep learning and ML models using cloud technologies (e.g., Azure Databricks, MLFlows and Azure ML)
Write production-ready modeling code that can be scaled out to 100 millions of calls and millions of users Collaboration.
Promote deep scientific expertise, constant learning, attention to detail, and best practices while always being friendly, humble, and open to challenging any assumptions.
Collaborate with data engineers, machine learning engineers, product managers and capability teams to coordinate timely deployments from conception to release
Promotes and integrates best practices in data science and adheres to established work standards Other
Research new machine learning solutions to complex business problems
Communicate process, requirements, assumptions and caveats of advanced ML and NLP concepts and deliverables in laymen languages to non-technical business leaders Experience:
BS, MS, or PhD in Computer Science, Statistics, Applied Mathematics, Data Science, Economics or related quantitative fields
5+ years' experience in designing, developing and deploying production-grade machine learning solutions (supervised, unsupervised, reinforcement learning), deep learning.