Machine Learning Engineer

Job Summary
We are seeking a highly skilled and mathematically grounded Machine Learning Engineer to join our AI team. The ideal candidate will have 5+ years of ML experience with a deep understanding of machine learning algorithms, statistical modeling, and optimization techniques, along with hands-on experience in building scalable ML systems using modern frameworks and tools.________________________________________Key ResponsibilitiesDesign, develop, and deploy machine learning models for real-world applications.Collaborate with data scientists, software engineers, and product teams to integrate ML solutions into production systems.Understand the mathematics behind machine learning algorithms to effectively implement and optimize them.Conduct mathematical analysis of algorithms to ensure robustness, efficiency, and scalability.Optimize model performance through hyperparameter tuning, feature engineering, and algorithmic improvements.Stay updated with the latest research in machine learning and apply relevant findings to ongoing projects.________________________________________Required QualificationsMathematics & Theoretical FoundationsStrong foundation in Linear Algebra (e.g., matrix operations, eigenvalues, SVD).Proficiency in Probability and Statistics (e.g., Bayesian inference, hypothesis testing, distributions).Solid understanding of Calculus (e.g., gradients, partial derivatives, optimization).Knowledge of Numerical Methods and Convex Optimization.Familiarity with Information Theory, Graph Theory, or Statistical Learning Theory is a plus.Programming & Software SkillsProficient in Python (preferred), with experience in libraries such as:o NumPy, Pandas, Scikit-learn, Matplotlib, SeabornExperience with deep learning frameworks:o TensorFlow, PyTorch, Keras, or JAXFamiliarity with ML Ops tools:o MLflow, Kubeflow, Airflow, Docker, KubernetesExperience with cloud platforms (AWS, GCP, Azure) for model deployment.Machine Learning ExpertiseHands-on experience with supervised, unsupervised, and reinforcement learning.Understanding of model evaluation metrics and validation techniques.Experience with large-scale data processing (e.g., Spark, Dask) is a plus.________________________________________Preferred QualificationsMasters or Ph.D. in Computer Science, Mathematics, Statistics, or a related field.Publications or contributions to open-source ML projects.Experience with LLMs, transformers, or generative models.

Remote (Chennai - possible to travel Chennai for meetings)