**Requirements and responsibilities** **Duties:** * Design, develop, and deploy advanced AI/ML models for real\-world applications. * Lead end\-to\-end AI solution lifecycle: data collection, preprocessing, modeling, evaluation, and deployment. * Collaborate with data scientists, software engineers, and product managers to integrate AI into products. * Implement MLOps best practices for automation, monitoring, and retraining of models. * Research and evaluate new AI/ML frameworks, tools, and algorithms to enhance solutions. * Ensure scalability, performance, and reliability of AI systems in production. * Mentor and guide junior engineers to improve team capabilities. **Technical Requirements:** * Education: Bachelor’s or master’s in computer science, AI, Machine Learning, Data Science, or related field. * Experience: 5\+ years in AI/ML engineering with proven project deployment. * Programming: Strong proficiency in Python; knowledge of R, Java, or C\+\+ is a plus. * Frameworks \& Libraries: TensorFlow, PyTorch, scikit\-learn, Hugging Face, OpenAI APIs. * MLOps \& Deployment: CI/CD pipelines, Docker, Kubernetes, cloud platforms (AWS, Azure, GCP). * Data \& Databases: Experience with SQL/NoSQL, data preprocessing, big data tools (Spark, Hadoop). * APIs \& Integration: Experience building REST APIs / microservices for model deployment. **Non\-Technical Requirements:** * Strong problem\-solving and analytical skills. * Ability to prioritize tasks and manage time effectively. * Excellent verbal and written communication skills. * Strong collaboration and teamwork mindset. * Demonstrated proactivity, ownership, and commitment to deliver results. * Interest in continuous learning and professional development. * Ability to mentor junior engineers and foster knowledge\-sharing culture.