ML Engineer

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Date: Nov 15, 2024

Location: India, Coimbatore , IN

Company: Responsive

About Responsive

Responsive, formerly RFPIO, is the market leader in an emerging new category of SaaS solutions called Strategic Response Management. Responsive customers including Google, Microsoft, Blackrock, T.Rowe Price, Adobe, Amazon, Visa and Zoom are using Responsive to manage business critical responses to RFPs, RFIs, RFQs, security questionnaires, due diligence questionnaires and other requests for information. Responsive has nearly 2,000 customers of all sizes and has been voted “best in class” by G2 for 13 quarters straight. It also has more than 35% of the cloud SaaS leaders as customers, as well as more than 15 of the Fortune 100. Customers have used Responsive to close more than $300B in transactions to-date.

About the Role

Responsive is looking for an ML Engineer with a strong background in Python, NLP, structured and unstructured data, and basic understanding of ML and DL algorithms/frameworks. The ideal candidate will have a Bachelor's degree in any quantitative discipline, such as Engineering, Computer Science, IT, or Statistics. The ML Engineer should be familiar with Linux and Git and have strong problem-solving and analytical skills. Additionally, the candidate should have a good understanding of mathematics.

Essential Functions

  • To develop and implement ML models and algorithms that improve the company's products and services.

  • To Work with large datasets to analyze, model, and interpret data.

  • To create and optimize NLP models to extract meaningful insights from unstructured text data.

  • To collaborate with cross-functional teams to identify and solve complex business problems.

  • To continuously monitor and improve the performance of ML models.

  • To develop and maintain ML codebase, including version control using Git.

Education

  • Bachelor's degree in any quantitative discipline, such as Engineering, Computer Science, IT, or Statistics.

Experience

  • 3-5 years of experience in Machine Learning 

  • Proficiency in Python is a must

Knowledge, Ability & Skills

  • Comfortable with NLP techniques.

  • Basic understanding of ML and DL algorithms/frameworks.

  • Familiarity with Linux and Git.

  • Good problem-solving and analytical skills.

  • Good understanding of mathematics.