• US Citizen

• Green Card

• EAD (OPT/CPT/GC/H4)

• H1B Work Permit

• Corp-Corp

• W2-Permanent

• W2-Contract

• Contract to Hire

• Consulting/Contract

• UG :- - Not Required

• PG :- - Not Required

• No of position :- ( 1 )

• Post :- 10th Jul 2025

•            Working to solve some of the most challenging problems in natural language processing, machine learning, and information retrieval including topical classification, sentiment analysis, and user intent detection. 

•            Research, build, and deploy models based on both shallow and deep machine learning. Train robust NLP-based models on a very large corpus of news and financial data. 

•            Apply machine learning techniques for improving search algorithms. 

•            Drive best practices for NLP/Machine Learning pipelines. 

•            Maintain current knowledge base of state-of-the-art ML algorithms (BERT, ELMo, GPT, etc.), APIs, and open-source methods, able to quickly evaluate alternatives. 

•            Translate complex business requirements into actionable stories with reasonable time estimates. 

•            Work with product leaders to apply data science solutions. 

Skills:

•            In-depth understanding of machine learning techniques such as classification, clustering, recommendation systems, and statistical models. 

•            Experience using Machine Learning and associated packages like scikit-learn, pandas, and NumPy. 

•            Proficiency training large-scale models in at least one modern deep learning engine such as TensorFlow, Keras, PyTorch/Torch, MXNet, Caffe/Caffe2. 

•            Minimum 5 years of experience using NLP tools and methods such as OpenNLP, Stanford NLP, LDA, Gensim, spaCy. 

•            Minimum 5 years of recent coding experience using Python AND/OR (Java OR Scala). 

•            SQL programming experience. 

•            Experience and ability to design and work within complex data models. 

•            Strong skills in setting, communicating, implementing, and achieving business objectives and goals. 

•            Familiarity with Cloud-based Machine Learning environments, Spark, Visualization/Dashboarding, Elasticsearch, Solr, Graph DBs (i.e., Janus Graph, Neptune, etc.). 

•            Able to work well on a small team and lead other more junior members of the team.