ML Engineer

At Rhythm, our values serve as the cornerstone of our organization. We are deeply committed to customer success, fostering innovation, and nurturing our employees. These values shape our decisions, actions, and interactions, ensuring that we consistently create a positive impact on the world around us. Rhythm Innovations is currently looking for a skilled and enthusiastic Machine Learning (ML) Developer to conceptualize, create, and implement machine learning models that enhance our supply chain risk management and other cutting-edge solutions. As an ML Developer, you will collaborate closely with our AI Architect and diverse teams to construct intelligent systems that tackle intricate business challenges and further our goal of providing unparalleled customer satisfaction. Key Responsibilities Model Development: Devise, execute, and train machine learning models utilizing cutting-edge algorithms and frameworks like TensorFlow, PyTorch, and scikit-learn. Data Preparation: Process, refine, and convert extensive datasets for the training and assessment of ML models. Feature Engineering: Identify and engineer pertinent features to enhance model performance and precision. Algorithm Optimization: Explore and implement advanced algorithms to cater to specific use cases such as classification, regression, clustering, and anomaly detection. Integration: Coordinate with software developers to integrate ML models into operational systems and guarantee smooth functionality. Performance Evaluation: Assess model performance using suitable metrics and consistently refine for accuracy, efficacy, and scalability. MLOps: Aid in establishing and overseeing CI/CD pipelines for model deployment and monitoring in production environments. Research and Development: Stay abreast of the latest breakthroughs in Gen AI AI/ML technologies and propose inventive solutions. Collaboration: Engage closely with data engineers, product teams, and stakeholders to grasp requirements and deliver customized ML solutions. Requirements Educational Background: Bachelor's in Engineering in Computer Science, Data Science, Artificial Intelligence, or a related field. Experience: 3 to 6 years of practical experience in developing and deploying machine learning models. Technical Skills Proficiency in Python and ML libraries/frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Experience with data manipulation tools like Pandas, NumPy, and visualization libraries such as Matplotlib or Seaborn. Familiarity with big data frameworks (Hadoop, Spark) is advantageous. Knowledge of SQL/NoSQL databases and data pipeline tools (e.g., Apache Airflow). Hands-on experience with cloud platforms (AWS, Azure, Google Cloud) and their Gen AI AI/ML services. Thorough understanding of supervised and unsupervised learning, deep learning, and reinforcement learning. Exposure to MLOps practices and model deployment pipelines. Soft Skills Strong problem-solving and analytical abilities. Effective communication and teamwork skills. Capability to thrive in a dynamic, collaborative environment.,