We are looking for a professional who is passionate about ML and stays up-to-date with the latest developments in the field.
Responsibilities
Applying machine learning, deep learning, and signal processing on large datasets (Audio, sensors, images, videos, text) to develop models.
Architecting large-scale data analytics/modeling systems.
Designing and programming machine learning methods and integrating them into our ML framework/pipeline.
Analyzing data collected from various sources.
Evaluating and validating the analysis with statistical methods. Also presenting this in a lucid form to people not familiar with the domain of data science/computer science.
Writing specifications for algorithms, reports on data analysis, and documentation of algorithms.
Evaluating new machine learning methods and adapting them as per project needs. Feature engineering to add new features that improve model performance.
Follow secure development, testing, and deployment guidelines and practices to adhere to the overall security of the system under consideration.
Requirements
B.E.\B. Tech\B.S. candidates' entries with significant knowledge in the aforementioned fields will be considered.
Background and knowledge of recent advances in machine learning, deep learning, natural language processing, and/or image/signal/video processing.
Strong programming background, e.g. Python, C/C++, R, Java, and knowledge of software engineering concepts (OOP, design patterns).
Knowledge of machine learning libraries TensorFlow, Jax, Keras, scikit-learn, PyTorch.
Excellent mathematical skills and background, e.g. accuracy, significance tests, visualization, and advanced probability concepts.
Ability to perform both independent and collaborative research.
Excellent written and spoken communication skills.
A proven ability to work in a cross-discipline environment in defined time frames.
Knowledge and experience in deploying large-scale systems using distributed and cloud-based systems (Hadoop, Spark, Amazon EC2, Dataflow) is a big plus.