ML Engineer

Job Description

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 Responsibilities To develop and implement ML models and algorithms that improve the company's products and services, To Work with large datasets to analyse, 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,