AI/ML Associate Manager

### **Role Overview** As an **AI/ML Engineer Associate Manager**, you will design, build, and deploy scalable Artificial Intelligence (AI) and Machine Learning (ML) solutions that enable organizations to unlock value from data and advanced analytics. You will leverage cloud\-native AI services, Generative AI technologies, and MLOps best practices to deliver production\-ready solutions while driving innovation through research, model development, and high\-performance computing capabilities. **Key Responsibilities** ------------------------ * Design and develop AI and Machine Learning solutions using modern AI frameworks and cloud\-based AI services. * Build, deploy, and maintain scalable data pipelines that support model training, inference, monitoring, and production operations. * Implement DevOps and MLOps practices to ensure efficient model development, deployment, versioning, and lifecycle management. * Customize, fine\-tune, and deploy Deep Learning, Generative AI, and Large Language Model (LLM) solutions to address business requirements. * Develop AI solutions that can operate across cloud environments, edge devices, and High\-Performance Computing (HPC) infrastructures. * Evaluate model performance and communicate the quality, scalability, and business value of AI solutions to stakeholders. * Conduct research and development activities focused on emerging AI technologies, algorithms, simulations, and advanced analytical methods. * Work with large\-scale structured and unstructured datasets, applying data cleansing, preprocessing, feature engineering, and optimization techniques. * Design and implement efficient data, model, and knowledge storage mechanisms to support AI applications and retrieval capabilities. * Collaborate with architects, data engineers, and business stakeholders to deliver robust, enterprise\-grade AI solutions. * Ensure adherence to security, governance, and Responsible AI principles throughout the AI solution lifecycle. * Support continuous improvement of AI platforms, tools, and engineering practices to enhance solution performance and reliability. **Basic Qualifications** ------------------------ * **6\-9 years of experience** in Artificial Intelligence, Machine Learning, Data Science, Data Engineering, or related technical fields. * Hands\-on experience designing, developing, and deploying AI/ML solutions in enterprise environments. * Strong programming experience in Python and AI/ML frameworks such as TensorFlow, PyTorch, Scikit\-learn, or equivalent technologies. * Experience working with Deep Learning, Generative AI, Large Language Models (LLMs), and advanced analytics solutions. * Knowledge of cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform and their AI/ML services. * Experience building scalable data pipelines and implementing MLOps practices for model deployment and monitoring. * Strong understanding of data engineering, data preprocessing, feature engineering, and model optimization techniques. ### **Preferred Qualifications** * Experience developing and deploying Generative AI solutions, foundation models, and LLM\-based applications. * Knowledge of Retrieval\-Augmented Generation (RAG), vector databases, embeddings, and AI orchestration frameworks. * Experience with containerization technologies such as Docker and orchestration platforms such as Kubernetes. * Familiarity with edge AI deployments, distributed computing architectures, and High\-Performance Computing (HPC) environments. * Experience implementing AI observability, model monitoring, and production support processes. * Strong analytical, problem\-solving, and stakeholder management skills. * Relevant certifications in Artificial Intelligence, Machine Learning, Data Engineering, or Cloud Technologies are preferred.