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.

KeyResult Areas include:

Lead and drive execution of new initiatives for Machine Learning using conversational NLP techniques and introduce ML-based learning for recommendation and coaching assistant in our products

Lead team of ML engineers in evaluating ML technologies, building/training models, deployment of models and monitoring in production environments.

Work 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

YouAre:

A driven team player, collaborator, and relationship builder whose infectious can-do attitude inspires others and encourages excellent performance in a fast-moving environment.

Results orientated, motivated by success.

Self-motivated: You can work with minimal supervision and be able to strategically prioritize multiple tasks proactively.

Whatyou need:

Master's or bachelor's degree in computer science or a related study or equivalent experience.

7+ years of hands-on experience architecting and designing highly scalable and resilient systems.

5+ years of experience in designing & scaling applications based on Data Science, NLP, and conversational AI

Understanding of ML algorithms - classical and deep learning and ML frameworks

Good understanding of system availability, security, and performance management.

In particular, the candidate shouldhave work experience with:

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

Besides this, the candidate must possess a mature

understanding of, and hands-on experience in, the broad field of

machine-learning and statistical methods. Must be conversant with:

scikit-learn

Pandas

Numpy

plotting using matplotlib, seaborn, etc.

HuggingFace

Beside

the knowledge of framework or libraries, having experience in building the

recommendation systems with following algorithms will be considered as a plus:

Generative Models i.e. VAE & GAN

Collaborative based filtering/ Context aware/Graph based recommender systems

Factorization Machine

Deep recommender

Experience

with any of the following is considered a plus:

Tensorflow

Big-data and PySpark

Data wrangling libraries: Beautiful Soup or Scrapy

R libraries

Taking models to production

Cloud Technologies: GCP/AWS

ML Graph Models GNN and NetworkX

Equal Employment Opportunity has been, and will continue to be, a fundamental commitment at Cornerstone OnDemand. All qualified applicants are given consideration regardless of race, color, gender, age, sexual orientation, national origin, marital status, citizenship status, disability, veteran status, or any other protected class as provided in applicable Federal, State, or Local fair employment laws. If you have a disability or special need that requires accommodation, please contact us at careers@csod.com