ML Engineer

You will be responsible for developing, training, and fine-tuning Machine Learning models for AI/ML applications. This includes designing and implementing data pipelines for data processing, model training, and inference. Additionally, you will be deploying models using MLOps and integrating them with cloud infrastructure. Collaboration with product managers and designers to conceptualize AI-driven features will also be a key part of your role. You will also be expected to research and implement various ML and AI techniques to improve performance. To excel in this role, you should have proficiency in Python and ML frameworks such as Scikit-learn, XGBoost, TensorFlow, PyTorch. Experience with SQL and ETL data pipelines, including data processing and feature engineering, will be beneficial. Familiarity with Docker and container-based deployments to create cloud-agnostic products is required. A strong understanding of AI and Machine Learning concepts such as Supervised Learning, Unsupervised Learning, Deep Learning, and Reinforcement Learning is essential. Knowledge of at least one cloud platform (AWS, Azure, GCP) and ML deployment strategies, preferably Azure, is preferred. Exposure to LLMs (e.g., OpenAI, Hugging Face, Mistral) and foundation models will be an advantage. Understanding of various Statistical models is also expected. If you have 5 to 7 years of experience in the relevant field and possess the mentioned skills and qualifications, we would like to hear from you.,