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Job Overview
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Date PostedAugust 15, 2023
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Location
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Expiration date--
Job Description
Responsibilities:
Design, Implement and Evaluate models and Design machine learning systems(NLP, text analytics, information retrieval, search, and recommendation systems, Knowledge graph, conversational system, Time-series based modelling, forecasting)
Design, development, evaluate and deploy innovative and highly scalable ML to improve the quality of products.
You should be passionate about working with data sets and be someone who loves to bring datasets together and use machine learning and analytical techniques to answer business questions and deliver actionable user-insights to build the best products and models.
Rapidly prototype integration of latest research in the field of ML/DL into the product.
Work closely with team of high performing data scientist and single ownership to identify opportunities, design, and assess improvements to ML Engine & Products
Role Skills:
- 3-5 years of hands-on experience in building machine learning systems for large datasets.
- Ability to break down and frame business problems into data science solutions and hands-on capability to create MVP out of it and run a DS project end to end independently.
- In-depth knowledge on supervised and unsupervised machine learning algorithms including classification, clustering, and regression.
- Experience in NLP (Sequence segmentation, Labeling and parsing, Knowledge extraction, Question answering, Multi text learning, ontology, taxonomy building), Machine Learning.
- Experience in Entity Extraction, Entity Linking, Clustering algorithms.
- Proficient in Math & Deep Learning (VAE, RNN, LSTM, CNN, attention models, Transfomer etc.), machine learning(svm, random forest), Clustering, topic modeling(LDA, LSA) and graph models.
- Experience in Python, Scikit-learn, Pytorch, Keras, Tensorflow
- Experience of implementing Deep Learning models into production
- Familiarity with distributed computing.
- Experience with SQL and/or No-SQL modelling.
- Excellent communication, analytical and problem-solving skills.
- B.S./B.S.E./MS degree in Applied Math, Data Science, Computer Science, Physics, or Similar Technical Field
Preferred Qualifications
- Passion to dive deep to resolve problems at their root.
- Experience in Data Governance, Data quality, Model Governance & MLops is a huge plus. Functional knowledge of platforms such as MLFLOW, Hopsworks/Sagemaker feature store/feast/Tecton, Seldon, DVC.
- Experience on building fair & explainable ML based product.
- Experience on federated learning, differential privacy, reinforcement learning.
- Experience on A/B testing, federated learning, differential privacy.
- Experience of git, flask, restful APIs.
- Experience working in a fast-paced, high tech environment.