MLOps Engineer

Responsibilities

• Design and develop machine learning models for recommendation systems, sentiment analysis, and content personalization
• Deploy machine learning solutions to meet enterprise goals and support experimentation
• Ensure enterprise infrastructure and data pipelines are equipped to support ML solutions
• Implement and optimize machine learning algorithms to improve performance and accuracy
• Collaborate with data scientists, engineers, and stakeholders to translate business requirements into ML solutions
• Design and implement scalable machine learning pipelines for preprocessing, training, and deployment
• Monitor and analyze model performance and implement enhancements
• Research latest advancements in machine learning and AI technologies
• Mentor and guide junior machine learning engineers
• Translate business needs into machine learning problem statements and specific deliverables
• Work with UX designers and product teams to improve user experience

Requirements

• Bachelor's or master's degree in Computer Science, Engineering, Mathematics, or a related field
• 3-6 years of experience in machine learning with a track record of production deployment
• Strong understanding of algorithms including classification, regression, clustering, and deep learning
• Proficiency in Python, R, or Javascript
• Knowledge of TensorFlow, PyTorch, or scikit-learn
• Familiarity with AWS SageMaker, Google Cloud AI, or Azure Machine Learning
• Expertise in data structures, algorithms, and software design patterns
• Excellent communication and collaboration skills

About the Company

Saarthee specializes in delivering data-driven insights through analytics consulting. Their work includes data engineering, data science, and machine learning solutions, tailored to client needs using a tool-agnostic approach.