AI & Machine Learning Consultant

Role Overview As an AI & Machine Learning Consultant , you will design, build, and deploy innovative Artificial Intelligence (AI) and Machine Learning (ML) solutions that help organizations solve complex business challenges. You will leverage cloud-native AI services, Generative AI technologies, and modern engineering practices to develop scalable, production-ready solutions. Working across the full AI lifecycle, you will transform data into intelligent applications while driving innovation through advanced analytics, model development, and AI research initiatives. Key Responsibilities Design and develop Artificial Intelligence (AI) and Machine Learning (ML) solutions using cloud-based AI platforms and services. Build and maintain scalable data pipelines that support data ingestion, model training, deployment, and production operations. Implement DevOps and MLOps practices to automate and streamline model development, deployment, monitoring, and maintenance. Develop, customize, and deploy Deep Learning, Generative AI, and Large Language Model (LLM) solutions tailored to business requirements. Evaluate business needs, data availability, and infrastructure constraints to design effective AI solutions that deliver measurable value. Support the development of AI applications across cloud, edge computing, and High-Performance Computing (HPC) environments. Conduct research and experimentation on emerging AI techniques, algorithms, models, and advanced analytical approaches. Work with large-scale structured and unstructured datasets, applying data cleansing, preprocessing, and feature engineering techniques to improve solution quality. Design and maintain efficient data, model, and knowledge storage solutions to support AI applications and retrieval capabilities. Collaborate with data engineers, architects, and business stakeholders to develop scalable and production-ready AI solutions. Monitor model performance and support continuous improvements to ensure reliability, scalability, and business impact. Ensure compliance with enterprise security, governance, and Responsible AI standards throughout the AI development lifecycle. Desired Candidate Profile 4-7 years of experience in Artificial Intelligence, Machine Learning, Data Science, Data Engineering, Analytics, or related technical fields. Hands-on experience developing and deploying AI/ML solutions in enterprise or consulting environments. Strong programming skills in Python and experience with machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, or similar 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 data pipelines and supporting MLOps practices for model deployment and lifecycle management. Strong understanding of data preprocessing, feature engineering, model evaluation, and optimization techniques. Experience developing and deploying Generative AI, LLM, or intelligent automation solutions. 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 model monitoring, observability, and AI operational support capabilities. Strong analytical, problem-solving, and stakeholder management skills. Relevant certifications in Artificial Intelligence, Machine Learning, Data Science, Cloud Platforms, or related technologies are preferred.