About AlphaSense:

AlphaSense is a search engine for market intelligence that transforms how decisions are made by the world’s leading corporations and financial institutions. Leveraging AI and NLP technology, AlphaSense enables knowledge professionals to extract insights in seconds from thousands of disparate data sources, including company filings, event transcripts, news and trade journals, and equity research. Founded in 2011 and backed by investors including Innovation Endeavors and Soros Fund Management, AlphaSense is on a mission to empower organizations to make data-driven decisions with confidence.

Check out what we’ve built so far: https://vimeo.com/360622663/fa460b394e

What You’ll Do:

  • Develop highly scalable deep learning and natural language processing models and take them all the way to production
  • Work closely with cross-functional teams to translate product requirements into machine learning algorithms and architectures
  • Work with other AI researchers to perform cutting edge research in deep learning, machine learning & natural language processing
  • Own systems end-to-end including design, code, training, testing, deployment and iteration

Who You Are:

  • You possess an advanced degree in Computer Science, Computer Engineering or relevant field from IITs/NITs/BITS or other Tier I colleges with a focus on machine learning, but equivalent industry experience may be considered.
  • An expert in machine learning and deep learning with min 2+ years of exp. Also, familiar with the state-of-the-art deep learning and natural language processing research.
  • Experience in developing end-to-end NLP models using Python and NLP libraries like Spacy and HuggingFace.
  • Proficient in writing high quality code and tests in Python. 
  • An excellent communicator with strong organizational, problem-solving, debugging and analytical skills
  • Familiar with deep learning frameworks like PyTorch and TensorFlow
  • Proficient in Java is not mandatory but a huge plus.
  • Familiar with working with cloud computing (preferably AWS or GCP)

 

 

 

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