Cornerstone provides an AI-powered Talent Experience Platform for unified content discovery, knowledge management, and personalized learning platform for your career journey. Our award-winning Platform is used globally by Fortune 500 companies and government organizations to solve content discovery, curation, and recommendation problems across external, internal, and tacit knowledge sources.
In the Data Science and Machine Leaning team at Cornerstone we are looking for solid hands-on technologists with solid time-management skills and experience in highly autonomous roles. You also function effectively in a collaborative environment and are comfortable making independent decisions.

This would be Mumbai/ Pune/ Hyderabad/Bangalore based role.

 In this role, you will…

Work on new initiatives for Machine Learning using conversational NLP techniques and introduce ML-based learning for recommendation and coaching assistant in our productsWork with the engineering teams and ensure timely deliveries.Be part of a global Engineering team supporting Fortune 1000 customers worldwide.Ability to experiment and iterate rapidly and provide tangible improvements in the overall engagement

You have got what it takes if you have…

Master's or bachelor's degree in computer science or a related study or equivalent experience.Understanding of ML algorithms - classical and deep learning and ML frameworksGood understanding of system availability, security, and performance management.Hand-s on work experience in: PyTorch and its ecosystem of libraries, Word and document embeddings, Transformers and Attention, RNN, LSTM, A background in BERT and its variants, transfer-learning practices, NLP Libraries: NLTK, Genism , Spacy, ML-pipelines – Apache Airflow/ Kubeflow/ RAY, OpenAI libraries and Models – LLMs, scikit-learn, Pandas, Numpy , plotting using matplotlib, seaborn, HuggingFace.

Experience with any of the following is considered a plus:

TensorFlow, Big-data and PySparkCloud Technologies: GCP/AWSML Graph Models GNN and NetworkXBuilding Recommendation Systems with Deep learning or GenAI modelsGenAI, using pretrained LLMs, finetuning of LLMs, prompt engineering and Multi-modelConversation agent framework with LangChain or RASA NLU etc.