Machine Learning Specialist

As a Machine Learning Engineer in Bangalore, you will be responsible for developing and implementing machine learning models to drive business solutions. Your primary qualifications should include a Master's degree in computer science, machine learning, data science, electrical engineering, or a related quantitative field. Additionally, you should have at least 5 years of professional experience in machine learning engineering, software engineering with a focus on ML, or a similar role. Key Responsibilities: - Demonstrate expert-level proficiency in Python, specifically in writing production-grade, clean, efficient, and well-documented code. Knowledge of other languages like Java, Go, or C++ is advantageous. - Utilize strong software engineering fundamentals, including a deep understanding of software design patterns, data structures, algorithms, object-oriented programming, and distributed systems. - Apply theoretical and practical knowledge of various machine learning algorithms, with proficiency in ML frameworks such as PyTorch and Scikit-learn. - Handle data effectively by working with SQL and NoSQL databases, understanding data warehousing concepts, and processing large datasets. - Utilize problem-solving skills to analyze and address complex technical challenges, delivering pragmatic solutions. - Communicate effectively through strong verbal and written skills, capable of explaining technical concepts to both technical and non-technical audiences. Qualifications Required: - Masters degree in computer science, machine learning, data science, electrical engineering, or a related quantitative field. - 5+ years of experience in machine learning engineering, software engineering with a focus on ML, or a similar role. - Expert-level proficiency in Python, with experience in writing clean, efficient, and well-documented code. Knowledge of other languages like Java, Go, or C++ is a plus. - Strong understanding of software design patterns, data structures, algorithms, object-oriented programming, and distributed systems. - Knowledge of machine learning algorithms, ML frameworks such as PyTorch and Scikit-learn, feature engineering, model evaluation metrics, and hyperparameter tuning. - Experience with SQL and NoSQL databases, data warehousing concepts, and processing large datasets. - Excellent analytical and problem-solving skills, with the ability to deliver pragmatic solutions. - Strong verbal and written communication skills to convey complex technical concepts effectively.,