Summary

An Associate Machine Learning (ML) Scientist at Wadhwani AI will build scientifically rigorous and robustly evaluated AI solutions that will be deployed in order to bring AI to the benefit of underserved billions across the developing world.

About Us

Wadhwani AI is a nonprofit institute building and deploying applied AI solutions to solve critical issues in public health, agriculture, education, and urban development in underserved communities in the global south. We collaborate with governments, social sector organizations, academic and research institutions, and domain experts to identify real-world problems, and develop practical AI solutions to tackle these issues with the aim of making a substantial positive impact.

We have over 30+ AI projects supported by leading philanthropies such as Bill & Melinda Gates Foundation, USAID and Google.org. With a team of over 200 professionals, our expertise encompasses AI/ML research and innovation, software engineering, domain knowledge, design and user research.

In the Press:

• Our Founder Donors are among the Top 100 AI Influencers
• G20 India’s Presidency: AI Healthcare, Agriculture, & Education Solutions Showcased Globally.
• Unlocking the potentials of AI in Public Health
• Wadhwani AI Takes an Impact-First Approach to Applying Artificial Intelligence - data.org
• Winner of the H&M Foundation Global Change Award 2022
• Indian Winners of the 2019 Google AI Impact Challenge, and the first in the Asia Pacific to host Google Fellows
  
  
  

Roles And Responsibilities

• As an Associate ML Scientist, you will be responsible for building robust machine learning solutions to problems of societal importance, usually under the guidance of senior ML scientists. You will participate in translating a problem in the social sector to a well-defined AI problem, in the development and execution of algorithms and solutions to the problem, in the successful and scaled deployment of the AI solution, and in defining appropriate metrics to evaluate the effectiveness of the deployed solution.
• In order to apply machine learning for social good, you will need to understand user challenges and their context, curate and transform data, train and validate models, run simulations and broadly derive insights from data. In doing so, you will work in cross-functional teams spanning ML modeling, engineering, solution and domain experts. You will also interface with social sector organizations as appropriate.
  
  
  

Requirements

• Associate ML scientists will have a strong academic background in a quantitative field (see below) at the Bachelor’s or Master’s level, with project experience in applied machine learning. They will possess demonstrable skills in coding, data mining and analysis, and building and implementing ML or statistical models. Where needed, they will have to learn and adapt to the requirements imposed by real-life, scaled deployments.
• Candidates should have excellent communication skills and a willingness to adapt to the challenges of doing applied work for social good.
  
  
  

Desired Qualifications

• B.Tech./B.E./B.S./M.Tech./M.E./M.S./M.Sc. or equivalent in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, Physics, Economics or a relevant quantitative field. Work experience beyond the terminal degree will determine the appropriate seniority level.
• Solid software engineering skills across one or multiple languages including Python, C++, Java.
• Interest in applying software engineering practices to ML projects.
• Track record of project work in applied machine learning. Experience in applying AI models to concrete real-world problems is a plus.
• Strong verbal and written communication skills in English.
  
  
  

Preferred Qualifications

• 1+ years of experience working with audio and speech technologies such as audio signal processing, automatic speech recognition, speaker identification and verification.
• Proficiency in working with HF Transformers and PyTorch.
• Worked on and deployed a machine learning service at scale.
  
  
  

We are committed to promoting diversity and the principle of equal employment opportunity for all our employees and encourage qualified candidates to apply irrespective of religion or belief, ethnic or social background, gender, gender identity, and disability. If you have any questions, please email us at .