Join CleverGround as a Machine Learning Engineer to build production-grade ML systems that power our global teaching platform. Work on classifiers, recommenders, and predictive models at scale.

About the Company

CleverGround Technologies is an education infrastructure startup on a mission to democratize education by empowering educators. We have built the largest global teaching-exclusive platform, enabling millions of teachers in India and across the world to digitize their classrooms with our proprietary, mobile-first classroom technology. In just over a year, we have onboarded 8 million users with a small, focused engineering team of just 12 people. Our platform processes over 30 million hours of live interaction every month, generating 4 petabytes of data. We have built our own video conferencing solution from scratch, starting from WebRTC implementation to QoS-based bandwidth control RFCs, and we continue to innovate with features like live whiteboard, live annotations, hand raise, and more. We are a team of young, enterprising leaders with experience at some of India's leading startups, united by a passion for innovation, ownership, and impact.

Role Overview

We are looking for a Machine Learning Engineer who will design and implement production-grade ML systems that power our educational platform. You will work on a variety of challenges including building classifiers, recommenders, predictive models, and multivariate optimization algorithms on large-scale datasets. This role requires a strong foundation in machine learning, statistical modeling, and distributed computing. You will collaborate closely with our data engineering team to ensure our ML systems are robust, scalable, and efficient. We value engineers who are eager to learn about real-world ML systems, have excellent analytical and problem-solving skills, and can thrive in a fast-paced, high-performing environment.

Key Responsibilities

• Design and implement production-grade machine learning systems.
• Develop classifiers, recommenders, predictive models, and multivariate optimization algorithms on large-scale datasets using advanced statistical modeling, machine learning, and data mining techniques.
• Work with the data engineering team to enable robust decision-making, considering scale, latency, and throughput requirements.
• Create tools and systems to speed up the ML lifecycle, from experimentation to deployment.
• Articulate design and implementation choices to cross-functional teams, ensuring alignment and understanding.
• Evangelize operational excellence and reduce technical debt in ML systems.
• Contribute to the development of data-related products and services that enhance the teaching and learning experience.

Tech Stack

• Programming: Python (primary)
• Machine Learning: scikit-learn, TensorFlow or PyTorch (implied), NLP libraries (e.g., spaCy, NLTK)
• Statistical Modeling: Regression, classification, clustering, multivariate optimization
• Data Infrastructure: cloud platforms (AWS, GCP, or Azure), distributed computing (Spark, Hadoop)
• Data Pipeline: ETL tools, real-time streaming (Kafka, Kinesis)
• Databases: SQL, NoSQL (e.g., MongoDB, Cassandra)
• Additional: WebRTC (for video conferencing), multi-threaded programming, algorithms, data structures

We are looking for engineers with a co-founder mentality who are ready to lead the building of a product that is changing the face of education. If you are passionate about leveraging ML to create impactful learning experiences, we want to hear from you.

Bachelors or Masters in Computer Science/Electrical Engineering/Statistics or relevant field; 2+ years of experience as a Data Scientist or Machine Learning Engineer; Strong programming skills in Python or equivalent; Solid foundation in machine learning, NLP, classifiers, statistical modeling, and multivariate optimization; General understanding of data structures, algorithms, multi-threaded programming, and distributed computing concepts; Nice-to-have: Experience in scaling infrastructure to support high-throughput data-intensive applications; Must-have: Eager to learn about real-world ML systems, excellent analytical and problem-solving skills, self-starter with ability to work well in a high-performing team.

Competitive salary, opportunity to work with a small high-impact team, co-founder mentality, chance to build scalable ML systems from scratch, work on a product that is transforming education globally.