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ML Engineer

3 - 5 years

4 - 8 Lacs

Posted:3 weeks ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

About Responsive Responsive (formerly RFPIO) is the global leader in strategic response management software, transforming how organizations share and exchange critical information. The AI-powered Responsive Platform is purpose-built to manage responses at scale, empowering companies across the world to accelerate growth, mitigate risk and improve employee experiences. Nearly 2,000 customers have standardized on Responsive to respond to RFPs, RFIs, DDQs, ESGs, security questionnaires, ad hoc information requests and more. Responsive is headquartered in Portland, OR, with additional offices in Kansas City, MO and Coimbatore, India. Learn more at responsive.io . 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 Bachelors 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 companys 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 Bachelors 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.

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