ML Engineer

You will be responsible for designing, developing, and deploying machine learning models for real-world applications. Your main tasks will involve building and maintaining scalable ML pipelines using tools like Airflow, MLflow, or Kubeflow. Additionally, you will collaborate with data scientists, data engineers, and product teams to understand business needs and translate them into ML solutions. Data preprocessing, feature engineering, and model evaluation will be part of your routine to optimize model performance and ensure robustness, fairness, and explainability. Monitoring and maintaining models in production, including retraining and performance tracking, will also be essential. You will contribute to the development of internal ML tools and frameworks while staying up to date with the latest research and best practices in machine learning and MLOps. To excel in this role, you should have strong working experience in Python and hands-on experience in machine learning platforms, frameworks, and libraries. A deep understanding of Deep Learning concepts is crucial to conduct experiments and analyze results for optimizing model performance and accuracy. You must also possess a solid understanding of software engineering concepts to build robust and scalable AI systems. Additionally, you will be involved in conceiving, designing, and developing NLP concepts such as text representation, semantic extraction techniques, and modeling. Knowledge in building web apps/UI/Reporting using Python packages like PlotlyDash, Streamlit, and Panel with User-Centric design is considered advantageous. Familiarity with cloud-based AI/ML services is also desirable. In return, you will receive a competitive salary and performance-based bonuses, comprehensive insurance plans, and the opportunity to work in a collaborative and supportive environment. You will have the chance to learn and grow with a talented team while enjoying a positive and fun work environment.,