Off-campus drive 2020
BYJU’S is India’s largest Ed-tech company and the creator of India’s largest K12 learning app which offers highly adaptive, engaging, and effective learning programs for students in classes 4-12 (K-12) and competitive exams like JEE, NEET, CAT, IAS, GRE, and GMAT. Today, Byju’s has over 25 million downloads and 1.7 million annual paid subscriptions. With an average time of 64 minutes being spent by a student on the app every day, the Byju’s app is making learning enjoyable and effective.
Launched in 2015, Byju’s has become the most loved and preferred education app for students across age groups.
Delivering world-class learning experience, Byju’s is paving the way for new-age, geography-agnostic learning tools that sit at the cross-section of mobile, interactive content, and adaptive learning methodologies. The learning app makes use of original content, rich animations, interactive simulations, and engaging video lessons from India’s best teachers, which adapts to the unique learning style of every student.
At Byju’s our mission is to help children fall in love with learning. Our learning products have enabled millions of students across the globe to take the initiative to learn on their own
Responsibilities:
- Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress
- Managing available resources such as hardware, data, and personnel so that deadlines are met
- Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probability
- Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
- Verifying data quality, and/or ensuring it via data cleaning
- Supervising the data acquisition process if more data is needed
- Finding available data sets online that could be used for training
- Defining validation strategies Defining the pre-processing or feature engineering to be done on a given data set
- Defining data augmentation pipelines
- Training models and tuning their hyperparameters
- Analyzing the errors of the model and designing strategies to overcome them – Deploying models to production
Requirements:
- Proficiency with a deep learning framework such as Tensor Flow or Keras
- Proficiency with Python and basic libraries for machine learning such as sci kit-learn and pandas
- Expertise in visualizing and manipulating big data sets
- Proficiency with Open CV
- Familiarity with Linux
- Ability to select hardware to run an ML model with the required latency
