Job Description
Adamas Tech Consulting, a technology wing of the RICE group has been set up in Bengaluru with the vision of digitizing the entire aspect of education and skilling. Adamas Tech Consulting Pvt Ltd. wants to create a global learning platform that will bring affordable education to all individuals who aspire to learn. The Company will invite universities and corporates from across the world to offer, deliver and consume courses. The learning modules will be digitized by the company itself. It will enable students, learners, employees, and all other knowledge seekers to access the latest courses and skills available around the world. This platform will be amongst the first in the Indian market to be backed by an educational institution (Adamas University, Kolkata, India).
Link: https://www.ricesmart.in/adamas-tech-consulting/
Parent Company: https://www.ricesmart.in/
Skills Required:
- Tableau Software
- Python
- Machine Learning
- Django
- Docker
- GPU Computing
- SQL
- Relational Database Management System (RDBMS)
- TensorFlow and/or PyTorch Software Library
Requirements:
- Bachelor's/Master's degree in Computer Science/Computer Engineering/IT or related fields.
- 2+ years of experience. Exceptional candidates with less experience are welcome to apply.
- Industry experience working regression Model (Tensorflow, Keras, Model Training/Inference, etc).
- Strong experience with RDBMS and NoSQL databases and different datasets like Excel, CSV, JSON, etc...
- Strong experience with Python, R, and writing reusable code.
- Strong experience working with regression models and classification models.
- Experience working with pandas, Numpy, and Scikit packages and python visualization packages.
- Experience with Python web framework, e.g. Flask, Django or FastAPI
- Experience with different ML platforms: PyTorch,TensorFlow.
- Experience with utilizing various GPU-based training infrastructures.
- Experience with Docker
- Experience with Pyspark or Tableau.
Responsibilities:
- Understanding business objectives and developing software and models that help achieve them. The software could involve a training framework, - -inference framework, working with different technologies for ML.
- 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
- Develop processes for different common operations of the team: data acquisition, model training, and prototype development.
- Feature Engineering and Data Modeling.
- Transforming data science prototypes and applying appropriate ML algorithms and tools.
- Finding open-source datasets for prototype development.
- Training models and tuning their hyperparameters
- Analyzing the errors of the model and designing strategies to overcome them
- Data Visualization Tool Experience Pyspark, Tableau, etc.
- Training models and tuning their hyperparameters.