What Makes Wadhwani AI a Unique and Rewarding Place to Work At

360-degree diversity and a culture where agility, knowledge-sharing, and independence are highly valued. Here’s what makes Wadhwani AI a great place to work at.
As an organisation, we want to see our ideas translate into action, as soon as feasible.

At Wadhwani AI, we are a tight-knit team with a unique blend of skills and backgrounds. Decades-long industry experience meets youth, expertise, and innovation, as we work towards solving some of the biggest problems facing the developing world, using the power of modern AI. Our organisational culture values democracy, empowers all our employees, and enables both personal and professional growth. Here are some of the things that make the Wadhwani Institute for Artificial Intelligence a truly rewarding place to work at.

"The unique work culture that we have at Wadhwani AI is all about learning from each other."


It is not unusual at Wadhwani AI for a domain expert with over 30 years of experience and a research fellow who has just graduated from university to be on a team together. People with different skill-sets, career paths, and interests are colleagues, building on their own and each other’s strengths as they work towards common goals.


Constant learning is hardwired into our DNA, and is key to how we function. Every team member is keen to learn from a colleague, and share their own expertise as mentors. This is also encourages a culture of conversation and cross-pollination, which is vital for us because we work on diverse projects that require a constant exchange of ideas. Debates and discussions are generous, with everyone hearing one another out, and building opinions that take different points of view in account.

"We recognise that AI solutions need to work within existing systems and frameworks and work closely with partners and domain experts to complement our areas of expertise."


Wadhwani AI collaborates with some of the world’s finest institutes and organisations, and our team members attend conferences, workshops and other global events regularly. This offers the teams a chance to meet domain experts, peers and other interesting, accomplished people. The experience always adds to what each one brings to their work.


At every level, our teams are given the space and support to experiment with their ideas, and try something new. This freedom to chase a thought and see what it leads to allows for a sense of nimbleness that contributes to the impact our work has. If you believe that something you propose has value, you don’t have to hold back at Wadhwani AI. You can pitch your idea and ask for the resources. Evidence-based, structured thoughts are groomed in the organisation and also promoted within the culture.

"The people at Wadhwani AI are extremely open-minded—they are willing to hear you out, and have logical discussions rather than just stating their opinions. This has helped me a lot in developing my personality."


As an organisation, we want to see our ideas translate into action, as soon as feasible. This is particularly rewarding for team members, who get the opportunity to evaluate how the projects they work actually affect people and their lives.


As long as you get your work done, get it done right and on time, it doesn’t matter if you do it at the office, or from home or as you travel. Of course one is expected to be at the right meetings and meet their potential, but is a very democratic workplace. And this also means that when some of the junior researchers demanded that the office stock fruits and healthier snacks, the suggestion was taken up at once (though Bourbon biscuits continue to be the hottest items in the pantry.)

  • 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.