Key Responsibilities

• Design, architect, and implement end-to-end AI/ML solutions, from proof-of-concept to production deployment.
• Translate complex business problems into technical AI requirements and comprehensive solution designs.
• Integrate AI models into existing enterprise systems and develop robust APIs for AI-powered services.
• Perform MLOps activities including model deployment, monitoring, versioning, and pipeline automation.
• Collaborate with data scientists, software engineers, and product managers to ensure seamless integration and delivery.
• Provide technical expertise and support to clients, ensuring successful adoption and utilization of AI solutions.
• Stay current with emerging AI technologies, frameworks, and best practices, continuously improving solution offerings.

Required Skills & Experience

• Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.
• 3+ years of professional experience in AI/ML engineering, solutions architecture, or MLOps.
• Proficiency in Python and relevant AI/ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Pandas).
• Hands-on experience with cloud platforms (AWS, Azure, GCP) for deploying and managing AI/ML workloads.
• Solid understanding of MLOps principles and tools (e.g., Docker, Kubernetes, CI/CD, MLflow, Kubeflow).
• Strong software engineering fundamentals, including API design, data structures, algorithms, and version control (Git).
• Experience with data processing, database technologies (SQL/NoSQL), and ETL pipelines.
• Excellent problem-solving, analytical, and communication skills, with the ability to articulate complex technical concepts.