Machine Learning Engineer


  • Full Time

Provide data-driven insights and creative solutions that lead to innovative improvements
in our AI platform and Model Library.

  • Identify and implement innovative approaches to advance Active Learning capabilities and NLP features in the platform
  • Own all steps of the solution implementation process and collaborate with team members
  • Identity opportunities and new ways to use AI for the benefit of our customers
  • Create solution proposals that addresses the potential improvements as well as scalability and practical feasibility
  • Develop detailed implementation plans and a clear testing and evaluation framework
  • Work with the engineering team on the full implementation within the platform
  • Generate data-driven insights to influence product roadmap
  • Develop best practices for the data science team that will allow us to try new ideas faster
  • PhD in Computer Science or a related field. Alternatively, MS in Computer Science and extensive relevant work experience
  • Industry experience with software development in Java, C# or Python
  • Strong programming skills in Java and Python Experience
  • 2+ years of industry work experience with machine learning (SVM, logistic regression, Deep Learning, Active learning) and NLP technologies.
  • Track record of creative solutions to NLP/ML problems, using valid experimental framework and defendable metrics
  • Practical experience with training and tuning models (SVM, Deep learning, NER, custom entity types)
  • Work experience with sentiment classification, social media data analysis

Hiring Policy

This job description reflects the present requirements of the position. As duties and responsibilities change and develop, the job description will be reviewed and subject to amendment.

Reveal is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Reveal does not discriminate in employment on the basis of race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factor.

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