AI/ML Associate Manager

Job Summary

Design, build, and deploy scalable Artificial Intelligence and Machine Learning solutions that enable organizations to unlock value from data and advanced analytics. Leverage cloud-native AI services, Generative AI technologies, and MLOps best practices to deliver production-ready solutions.

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 solutions to address business requirements
• Develop AI solutions that operate across cloud environments, edge devices, and High-Performance Computing 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, and advanced analytical methods
• Collaborate with architects, data engineers, and business stakeholders to deliver enterprise-grade AI solutions

Must haves

• 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, or Scikit-learn
• Experience working with Deep Learning, Generative AI, and Large Language Models
• 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

Nice to haves

• Experience developing and deploying Generative AI solutions, foundation models, and LLM-based applications
• Knowledge of Retrieval-Augmented Generation, vector databases, embeddings, and AI orchestration frameworks
• Experience with containerization technologies such as Docker and orchestration platforms such as Kubernetes
• Relevant certifications in Artificial Intelligence, Machine Learning, Data Engineering, or Cloud Technologies

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