Wadhwani AI Pest Management


Pest Management (the “App”) is a product of National Entrepreneurship Network (“NEN”/ We”).

NEN is an independent, non-profit research institute and global hub, developing AI solutions for social good. Amongst mission is to develop and apply AI-based innovations and solutions to a broad range of societal domains.

The app is designed to guide the farmers and associated third parties to identify the pest infestation to the crops.

The farmers and associated third parties engaged with NEN will be required to upload the pictures of the crops infested with pests and the app shall suggest what the farmer is required to do further (“Service”).

Towards the provision of the abovementioned Services, Pest Management may require you to provide certain pieces of information about yourself or your entity. Please read below the Privacy Policy that sets out the manner and terms of the treatment of the information so collected.


This Data Privacy Policy (“Policy”) sets out details of the data collected on this App and the treatment of the same. The Policy is drafted to maintain transparency and adhere to the legislation laid down.

Information collected

The App will be collecting the following information of the users:

● Name, Phone number, GPS, images taken using the app, user type (farmer, extension worker, or admin), village, district, state.
● Interactions in the app and language settings are also collected.

NEN is committed to protecting your personal information and strives to maintain the privacy of all personal information that NEN Suite will have access to.

Personal information refers to any information from which your identity/the identity of a person is apparent or can be reasonably ascertained. All other data collected, such as transaction history, cookies, browser information etc. will be referred to as ‘Additional Information’.

Together the Personal Information as well as the Additional Information shall be referred to as the Information.



a) Data Principal means the natural person to whom the personal data relates

b) Personal Data means data about or relating to a natural person who is directly or indirectly identifiable, having regard to any characteristic, trait, attribute or any other feature of the identity of such natural person, whether online or offline, or any combination of such features with any other information, and shall include any inference drawn from such data for the purpose of profiling.

c) Person includes—
1) an individual,
2) a Hindu undivided family,
3) a company,
4) a firm,
5) an association of persons or a body of individuals, whether incorporated or not,
6) the State, and
7) every artificial juridical person, not falling within any of the preceding sub-clauses;

d) Processing in relation to personal data, means an operation or set of operations performed on personal data, and may include operations such as collection, recording, organisation, structuring, storage, adaptation, alteration, retrieval, use, alignment or combination, indexing, disclosure by transmission, dissemination or otherwise making available, restriction, erasure or destruction.

e) Sensitive Personal Data means such personal data, which may, reveal, be related to, or constitute—
1) financial data;
2) health data;
3) official identifier;
4) sex life;
5) sexual orientation;
6) biometric data;
7) genetic data;
8) transgender status;
9) intersex status;
10) caste or tribe;
11) religious or political belief or affiliation.

Utilisation of the Information

The Information collected will be used for the following purposes:

● Towards the provision of the Service
● To verify your identity on the platform
● For internal data analysis and marketing operations
● Ensure adherence to legal and regulatory requirements for prevention and detection of frauds and crimes amongst others

Collection and Processing of Personal Data

We shall ensure that the Personal Data is collected and processed as prescribed in the law and the Data Principal or a guardian of such Data Principal, as the case may be, shall be informed regarding the use, storage and the purpose for which the data is collected. Further, to protect your privacy, you should not provide any other information that is not specifically requested or that you do not wish to share. The data shall be collected only to the extent deemed necessary and shall be processed only for lawful purpose. NEN shall provide the Data Principal a notice or execute an agreement containing details as may be required under the law in force and the consent of the Data Principal shall be taken.

NEN shall not continue with the processing of Personal Data if the consent is withdrawn by the Data Principal. However, no consent shall be obtained in cases where it is expressly provided by law.

The Data Principal can also access your Personal Data and in case you have concerns around handling of your Personal Data.

Disclosure of Information

The Policy shall apply to all the NEN employees, contractors, vendors, business partners, interns, associates who may receive personal information, have access to personal information/ data collected or processed by NEN.

The Policy shall be strictly adhered to by all the Third Parties who have access to or who have received any personal information and are expected to read, understand and abide by the Policy.

The protection of your privacy throughout the course of processing personal data as well as the security of all business data are important concerns to us. We process personal data that was gathered during your visit on our website and only in accordance with statutory regulations.

Usage of Cookies

NEN shall also collect your information/data whenever you visit our web site. The information shall contain your limited information. The cookies shall help us recognize you whenever you visit our website which shall help us direct you based on your interests. Thus, making your use more convenient. We shall also obtain your prior consent each time you visit the website. Your selection shall be saved in the cookie for a period of 90 days.
Data Security and Disposal of Data

The Personal Data shall be collected, stored and disposed off in accordance with the international Standard IS/ISO/IEC 27001. The audit shall be conducted by an independent auditor once a year. The Data Protection Officer shall ensure that the Personal Data is protected and all related systems are in accordance with the law in force. In the event of any non- compliance, concerned internal authority shall take appropriate action against such non- compliance.

The Personal Data shall be disposed off once the purpose is achieved in the manner as is legally permissible.

Applicable Law

This privacy policy is subject to the laws as applicable in the Republic of India.

Changes to this Policy

We may,from time to time update this Policy to keep abreast with new technologies, regulatory requirements, new practices among other reasons in accordance with the Applicable Law. We shall ensure that the updated /revised Policy is displayed on our website along with the date. Any changes to this Policy will become effective upon posting of the revised Policy on this page. Your continued use of the App following such revision constitutes your acceptance of the revised Policy in effect.

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.