Wadhwani AI has officially been named as the Artificial Intelligence Partner for the Central Tuberculosis Division of India

Wadhwani AI will collaborate with the CTD using Artificial Intelligence and Machine Learning to meet the goal of ending the threat of tuberculosis in India by 2025.
Wadhwani AI will collaborate with the CTD using Artificial Intelligence and Machine Learning to help the CTD in its goal of ending the threat of tuberculosis in India by 2025.

Tuberculosis is caused by a bacterium called Mycobacterium tuberculosis. The bacteria can attack any part of the body such as the kidney, spine, and brain, but usually attacks the lungs, in which case it is highly contagious. If not treated properly, tuberculosis can be fatal, and failure to adhere to the treatment program for tuberculosis can often result in deadlier, drug-resistant forms of the bacteria.

In 2018, there were an estimated 27.4 lakh tuberculosis cases and 4.2 lakh deaths in the country. It is estimated that as many as 10 lakh tuberculosis cases go unreported. More people die of tuberculosis than of HIV and malaria put together.

To address this challenge, the Government of India adopted the target of eliminating tuberculosis in India by 2025 as part of the National Health Policy in 2017. To achieve that goal, the Central Tuberculosis Division has developed the National Strategic Plan (NSP) for the elimination of tuberculosis. The NSP enumerates several challenges across the tuberculosis cascade of care and addresses them with interventions broadly categorised under Detect, Treat, Prevent, and Build.

The Ministry of Health and Family Welfare (MoHFW) and Wadhwani AI strongly believe that the power of modern Artificial Intelligence can be used to reinforce and strengthen the programs and interventions put into place as part of the NSP, and to greatly boost the effectiveness of the plan. It is for this purpose that the Central Tuberculosis Division and Wadhwani AI have combined their considerable strengths to work towards research, development, piloting, and deployment of AI-based solutions towards achieving the ambitious goal of eliminating tuberculosis by 2025.

“Developing AI for social good requires experience in working in the field with the communities whose problems we are trying to address. Even more important is working with local, state, and national level government organisations to create meaningful impact. It is for this reason that we are especially excited to be working with the Central Tuberculosis Division of India. Tuberculosis is one of the most heinous infectious diseases in the world. As the AI partner to the CTD, we aim to work on building AI-based solutions to address multiple challenges across the cascade of tuberculosis care in the country. We aim to make the CTD AI-ready in order to fulfill their mission to eradicate TB by 2025,” says Dr. P. Anandan, CEO of the Wadhwani Institute for Artificial Intelligence.

The collaboration will seek to identify possible interventions to address challenges and improve processes across the tuberculosis cascade of care and program management using Artificial Intelligence and Machine Learning, including, but not limited to, modeling novel methods of screening and diagnostics, enabling adherence to treatment programs and identifying predictors of adherence and outcomes, and decision support for care-givers intending continuous improvement in quality of care, including treatment prescription.

“At Wadhwani AI, we are thrilled to have this opportunity to make the CTD AI-ready. We’ve already had the benefit of meeting and collaborating with the CTD in Delhi and other states, which has given us a good idea of the scope of the challenge they’re facing. With this formal collaboration, we are now ready to apply our expertise in AI to accelerate the initiatives being led by the CTD, so that they are better equipped to meet their goal of eradicating TB in the country by 2025,” says Raghu Dharmaraju, VP of Products and Programs at Wadhwani AI.

  • Wadhwani AI

    We are an independent and nonprofit institute developing multiple AI-based solutions in healthcare and agriculture, to bring about sustainable social impact at scale through the use of artificial intelligence.


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.