Machine Learning Analyst

Summary
We are seeking a Machine Learning Analyst with a strong foundation in Engineering or a related Quantitative Sciences discipline. While prior experience in Machine Learning is not mandatory, candidates with exposure to Machine Learning and Deep Learning (if any) are expected to demonstrate a rigorous understanding of the concepts they are familiar with. The ideal candidate must be a quick learner and demonstrate strong analytical skills, clear thinking and structured problem-solving, strong quantitative aptitude, a willingness to learn, high self-motivation, and a diligent work ethic.

About Us
Wadhwani AI is a nonprofit institute building and deploying applied AI solutions to solve critical issues in public health, agriculture, education, and urban development in underserved communities in the global south. We collaborate with governments, social sector organizations, academic and research institutions, and domain experts to identify real-world problems, and develop practical AI solutions to tackle these issues with the aim of making a substantial positive impact.

We have over 30+ AI projects supported by leading philanthropies such as Bill & Melinda Gates Foundation and With a team of over 200 professionals, our expertise encompasses AI/ML research and innovation, software engineering, domain knowledge, design and user research.

In the Press:

• Our Founder Donors are among the Top 100 AI Influencers
• G20 India's Presidency: AI Healthcare, Agriculture, & Education Solutions Showcased Globally.
• Unlocking the potentials of AI in Public Health
• Wadhwani AI Takes an Impact-First Approach to Applying Artificial Intelligence -
• Winner of the H&M Foundation Global Change Award 2022
• Indian Winners of the 2019 Google AI Impact Challenge, and the first in the Asia Pacific to host Google Fellow

PRE-REQUISITES

• ML Analyst position is open to all with prior training in Engineering or any related Quantitative Sciences discipline
• No prior experience in Machine Learning or Deep Learning is required
• Candidates with exposure to ML/DL (if any) are expected to have a clear and rigorous understanding of the concepts they are familiar with
• Strong skills in data handling, and logical problem-solving
• Demonstrates a quick learning ability, and a strong work ethic
• Willingness to take on any task, learn new tools, and adapt to evolving project needs

Roles & Responsibilities

• Work closely with data to support the development of ML and DL solutions
• Conduct experiments under guidance and report results reliably
• Learn to derive insights from experimental outcomes and determine appropriate next steps
• Prepare, curate, and analyse datasets for training and evaluation
• Monitor incoming data streams and perform regular quality checks
• Assist in training and inference of ML models, including deep learning architectures
• Contribute to well-documented and maintainable codebases
• Document work clearly and consistently with high standards
• Communicate and present experimental findings and results clearly within the team
• Learn and apply best practices across ML development, coding, documentation, and experimentation
• Collaborate effectively with project teams to meet milestones and deliverables
• Proactively seek help and feedback when needed
• Work efficiently with tools like Unix, VS Code, GitHub, and Docker
• Develop proficiency with common ML tools and libraries such as Pandas, Scikit-learn, PyTorch, Excel (pivot tables), Matplotlib, Weights & Biases

DESIRED COMPETENSIES

• Demonstrates curiosity, humility, and a strong motivation to learn and grow
• Takes full ownership of tasks; highly diligent, detail-oriented, and accountable
• Willing to engage in all types of work from data cleaning and exploration to debugging and tooling
• Comfortable sitting with raw data to explore, understand and derive insights, and not just focused on modelling
• Proactively seeks guidance and independently builds knowledge when needed
• Approaches every task with a quality-first mindset; no task is considered beneath them
• Identifies recurring patterns and abstracts them into reusable, generalisable workflows
• Contributes across the entire ML lifecycle including data preparation, experimentation, and analysis
• Selects and applies appropriate tools; builds efficient, reliable, and repeatable processes
• Maintains a high standard of error-free work; reviews and validates work thoroughly
• Collaborates effectively with cross-functional teams
• Communicates clearly and constructively, with an emphasis on precision and clarity

We are committed to promoting diversity and the principle of equal employment opportunity for all our employees and encourage qualified candidates to apply irrespective of religion or belief, ethnic or social background, gender, gender identity, and disability. If you have any questions, please email us