AI for Social Impact

Wadhwani AI is a nonprofit, applied AI institute that develops and deploys artificial intelligence technology to address social challenges in low- and middle-income countries. 

We build and deploy AI solutions in partnership with local governments and civil society organisations to improve large-scale public programs. Through our solutions, AI becomes an enabling technology that bridges the gap between problems and solutions, augments human capabilities and provides advanced decision support.

Computer vision forms the core of several of our healthcare and agriculture solutions.

Pest Management

Our award-winning CottonAce solution guides smallholder cotton farmers on the optimal time to take preventive action and protect their farm against avoidable crop losses due to pests such as the Pink and American bollworm.

Newborn Anthropometry

To assist frontline health workers identify underweight neonates and monitor their growth, we are developing a smartphone-based technology that provides accurate, timely, geo-tagged and tamper-proof weight estimation.

Automating Diagnostic Tests for DR-TB

We use computer vision to automate the reading and interpretation of  Line Probe Assay test results to determine a tuberculosis patient’s drug sensitivity and types of drug resistance. Wadhwani AI is the official AI partner of India’s Central TB Division.

Teleradiology and Medical Imaging

We use computer vision to automate the reading of medical scans such as chest x-rays to identify lung diseases, ultrasound imagery to screen for tuberculosis, and are also excited to onboard new projects ranging from ophthalmology to dermatology to CT scans.

At Wadhwani AI, we work on AI problems that are unique and built for large-scale social initiatives. Their solutions are expected to impact millions across the developing world. While our current areas of focus are healthcare and agriculture, we are rapidly exploring other domains where AI technology can make a difference to the underserved.


We are hiring at all levels for our AI team to support our pace of growth, ranging from Associate ML Scientists with limited experience to Senior and Principal ML Scientists, as well as ML Engineers. These roles are commensurate with experience and will be evaluated on an individual basis.

Modeling work at WIAI calls for expertise in ML/DL for vision, sound, text, and tabular data, principled approaches to data cleaning and imputation, building data, inference and evaluation pipelines, and above all, a passion to develop AI solutions that can reach the masses and help improve peoples’ lives.

Interested? Please fill in your name and email address using the form below, and we’ll get back to you at the earliest.



If you don’t quite fit into the roles listed above, but are passionate about working with us in a tech role, please write to us at

ML Engineer


An ML Engineer at Wadhwani AI will be responsible for building robust machine learning solutions to problems of societal importance; usually under the guidance of senior ML scientists, and in collaboration with dedicated software engineers. To our partners, a Wadhwani AI solution is generally a decision making tool that requires some piece of data to engage. It will be your responsibility to ensure that the information provided using that piece of data is sound. This not only requires robust learned models, but pipelines over which those models can be built, tweaked, tested, and monitored. The following subsections provide details from the perspective of solution design:

Early stage of proof of concept (PoC)

  • Setup and structure code bases that support an interactive ML experimentation process, as well as quick initial deployments
  • Develop and maintain toolsets and processes for ensuring the reproducibility of results
  • Code reviews with other technical team members at various stages of the PoC
  • Develop, extend, adopt a reliable, colab-like environment for ML

Late PoC

This is early to mid-stage of AI product development

  • Develop ETL pipelines. These can also be shared and/or owned by data engineers
  • Setup and maintain feature stores, databases, and data catalogs. Ensuring data veracity and lineage of on-demand pulls
  • Develop and support model health metrics

Post PoC

Responsibilities during production deployment

  • Develop and support A/B testing. Setup continuous integration and development (CI/CD) processes and pipelines for models
  • Develop and support continuous model monitoring
  • Define and publish service-level agreements (SLAs) for model serving. Such agreements include model latency, throughput, and reliability
  • L1/L2/L3 support for model debugging
  • Develop and support model serving environments
  • Model compression and distillation

We realize this list is broad and extensive. While the ideal candidate has some exposure to each of these topics, we also envision great candidates being experts at some subset. If either of those cases happens to be you, please apply.


Master’s degree or above in a STEM field. Several years of experience getting their hands dirty applying their craft.


  • Expert level Python programmer
  • Hands-on experience with Python libraries
    • Popular neural network libraries
    • Popular data science libraries (Pandas, numpy)
  • Knowledge of systems-level programming. Under the hood knowledge of C or C++
  • Experience and knowledge of various tools that fit into the model building pipeline. There are several – you should be able to speak to the pluses and minuses of a variety of tools given some challenge within the ML development pipeline
  • Database concepts; SQL
  • Experience with cloud platforms is a plus

ML Scientist


As an ML Scientist at Wadhwani AI, 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, product, and domain experts. You will also interface with social sector organizations as appropriate.  


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. 


  • 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.