Hello, world!

Behind everything we do at Wadhwani AI is the belief that AI can help address the knowledge and expertise gap that limits progress in improving the lives of poor communities.
On Feb 18, 2018, we were fortunate to be inaugurated by the Hon. Prime Minister of India Shri. Narendra Modi along with the presence of the Hon. Chief Minister of Maharashtra Shri. Devendra Fadnavis, the His Excellency the Governor of Maharashtra Shri C. Vidyasagar Rao and the Hon. Education Minister of Maharashtra Shri Vinod Tawde.

Today we are at a new dawn of Artificial Intelligence. Yet, the idea that thought can be formalised and written down as a set of rules is as old as philosophy itself. One doesn’t have to look far – the Nyaya system of classical Indian philosophy directly addresses this. The creation of automatons that are capable of human-level intelligence has intrigued human civilisations in every place and time in history.

Today, thanks to a series of stunning breakthroughs in computing technology aimed at codifying knowledge and creating methods for learning from vast amounts of data and experience, we now have machines that surpass human ability in answering questions based on general and specialized knowledge and in playing complex games that involve strategy and intelligence. It is now almost a given that Artificial Intelligence will be intricately intertwined in every aspect of our lives.

Yet, for all the hype, the current and anticipated reach of AI – or at least of its benefits – will be limited to less than 50% of humanity – to those who are economically comfortable and are able to access it. More than half of humanity still lives in poverty or near-poverty and the vast power of AI is not likely to affect their lives.

Unless we do something about it.

The premise behind what we are doing at Wadhwani AI is the belief that AI can help address the knowledge and expertise gap that limits progress in improving the lives of poor communities.

Our mission is to develop and apply AI-based innovations and solutions to a broad range of societal domains including healthcare, agriculture, education, infrastructure, and financial inclusion. Ultimately our aim is to work with governments, social sector organisations, other innovators, and all other relevant stakeholders to transform the lives of the billions of poor, underserved people in India and the rest of the world.

We are fortunate to have two visionary brothers as our founder donors, who conceived the idea of creating an institute for applied AI research and innovation aimed at social good. Dr. Romesh Wadhwani and Sunil Wadhwani are successful tech entrepreneurs of Indian origin who live in the US and have independently built large companies in the technology domain.

We have now grown to a team of about 25, consisting of AI scientists, engineers and product managers; program directors; and a small partnerships team.

On Feb 18, 2018, we were fortunate to be inaugurated by the Hon. Prime Minister of India Shri. Narendra Modi along with the presence of the Hon. Chief Minister of Maharashtra Shri. Devendra Fadnavis, the His Excellency the Governor of Maharashtra Shri C. Vidyasagar Rao and the Hon. Education Minister of Maharashtra Shri Vinod Tawde.

The journey, which formally began that month, has accelerated rapidly and we are now finding ourselves in the midst of working on a number of exciting opportunities for developing AI for social impact. However, the two ends of this chain – namely problem identification and testing/deployment — require experience in working in the field with the communities whose problems we are trying to address. And, equally important is experience in working with local, state, and national level government organizations. For this we look for partners — typically (though not always) other NGOs, philanthropic organisations, domain experts and other stakeholders.

It was incredibly heartwarming and totally encouraging to find that there is a huge amount of interest and support from all stakeholders to see the power of AI applied to address key challenges. We have chosen specific solutions to address and are already well under way in collecting data, developing our technical approach and AI algorithms, and scheduling field tests in each problem area.

We have now grown to a team of about 25, consisting of AI scientists, engineers and product managers; program directors; and a small partnerships team. And we are rapidly building our technical infrastructure as well. If you come to our office in Andheri, Mumbai, you will see young researchers huddled together discussing AI technical problems while, on the other side, others are discussing the state of projects and programs or debating ethics or strategy with visiting international experts.

In closing, I would like to say that the time has come for AI to focus on social good and we are pleased to have the front seat in this journey.

Dr. P. Anandan
CEO, 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.

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ML Engineer

ROLES AND RESPONSIBILITIES

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.

DESIRED QUALIFICATIONS

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

Programming

  • 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
mle

ML Scientist

ROLES AND RESPONSIBILITIES

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.  

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.
mls