Machine Learning Engineer

Key Responsibilities Model Development: Design, train, and optimize machine learning models for production use. Architecture \& Scalability: Build robust, scalable ML pipelines and data processing systems. Research \& Innovation: Stay ahead of emerging AI/ML trends and integrate cutting\-edge techniques. Collaboration: Work closely with data scientists, software engineers, and product managers to align ML solutions with business goals. Mentorship: Guide and review the work of junior ML engineers and data scientists. Deployment \& Monitoring: Implement CI/CD for ML models, ensuring performance, reliability, and fairness. Required Skills Technical Expertise: Strong proficiency in Python, TensorFlow, PyTorch, scikit\-learn. Experience with cloud platforms (AWS, GCP, Azure) and MLOps tools. Deep understanding of NLP, Computer Vision, or Recommendation Systems. Strong grasp of data structures, algorithms, and distributed computing. Soft Skills: Excellent problem\-solving, leadership, and communication abilities. Preferred Experience Leading ML projects from concept to deployment. Working with big data technologies (Spark, Hadoop). Applying ethical AI and bias mitigation strategies.