ML Engineer

· Design, develop, and deploy machine learning models for real-world applications. · Build and maintain scalable ML pipelines using tools like Airflow, MLflow, or Kubeflow. · Collaborate with data scientists, data engineers, and product teams to understand business needs and translate them into ML solutions. · Perform data preprocessing, feature engineering, and model evaluation. · Optimize model performance and ensure robustness, fairness, and explainability. · Monitor and maintain models in production, including retraining and performance tracking. · Contribute to the development of internal ML tools and frameworks. · Stay up to date with the latest research and best practices in machine learning and MLOps. Requirements · Strong working experience in Python · Hands on Experience in machine learning platforms, frameworks, and libraries · Strong understanding of Deep Learning concepts and conduct experiments and analyze results to optimize model performance and accuracy · Strong understanding of software engineering concepts to build robust and scalable AI systems. · Conceive, design, and develop NLP concepts (text representation, semantic extraction techniques and modeling) · Knowledge in building web apps/UI/Reporting using Python packages like PlotlyDash, Streamlit and Panel etc. with User Centric design is an advantage. · Familiarity with cloud-based AI/ML services Benefits · Competitive salary and performance-based bonuses. · Comprehensive insurance plans. · Collaborative and supportive work environment. · Chance to learn and grow with a talented team. · A positive and fun work environment. Show more Show less