• Build and maintain robust ML applications using Python (Flask/FastAPI)
• Automate and manage ML lifecycle workflows, including data handling, model training, and model updates.
• Experience in using frameworks like Scikit-learn, TensorFlow, and PyTorch.
• Preprocess structured and unstructured data & construct optimized data pipelines to feed ML models.
• Customize and optimize popular large language models (LLMs).
• Apply advanced NLP techniques using Transformer architectures and Hugging Face libraries.
• Integrate data from MySQL and MongoDB databases.
• Ensure seamless deployment and management of ML models on Docker containers and Linux GPU servers.
• Run machine learning tests and experiments, and document findings and results.
• Analyzing the errors of the model and designing strategies to overcome them.

• Strong understanding of probability, and statistics as they apply to machine learning.
• Experience in EDA (Exploratory data analysis) for analyze & investigate data
• Experience in large scale data preprocessing, as well as working with structured and unstructured datasets.
• Manage codebases with version control systems like Git and GitHub.
• Knowledge of MLOps techniques as well as Kubernates, AWS/GCP and Redis-related knowledge will be a plus.
• Documentation on built ML applications with architectural diagrams.
• Remaining up to date on the latest innovations in machine learning.

Bachelor’s degree in Computer Science, Data Science, Statistics or a related field.

• Yearly two festival bonuses.
• Yearly increment based on performance 
• Lunch (partially subsidized) & free snacks.
• Friday off and 3 Saturdays off in a month.
• Annual, casual, medical, Maternity, and Training  leave as per company policy
• Training costs are paid by the company as per company policy
• Self-learning opportunities, professional training, sessions, and workshops took on new technology.
• Opportunity to work with a friendly and creative team.