Location - Remote ( Anywhere in USA )

Note- Need a write up from candidate about real time NLP technology use case in their project.

Model

• 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 Client algorithms and models using state-of-the-art techniques like deep learning neural networks (auto-encoders, feedforward networks, RNNs/CNNs, etc.) and NLP model Clienthitectures 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 Client solutions

Deployment

• Capture and inform your Client infrastructure decisions using your understanding of Client 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 Client models using cloud technologies (e.g., Clienture Databricks, MLFlows and Clienture Client)
• 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

• ReseClienth new machine learning solutions to complex business problems
• Communicate process, requirements, assumptions and caveats of advanced Client 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

framework (e.g. TensorFlow, PyTorch, Keras, etc) and NLP (NLTK, Spark NLP, spaCy, HuggingFace, Flair, NLTK, etc) for real-world business problems

• Expertise in Python and SQL, with working experience in Apache Spark, Hadoop, Databricks, Snowflake, or other big data systems
• Development and Client experience in cloud platforms such as Microsoft Clienture
• Combination of deep technical skills and business sense, to interface with all levels and disciplines within an organization.
• Excellent written and verbal communication skills to explain complex reseClienth to both technical and non-technical audiences
• Self-motivated individual that thrives in a dynamic environment