AI & Machine Learning Consultant

Job Summary

Design, develop, and deploy enterprise-grade AI and Machine Learning solutions that drive business innovation and operational efficiency. Leverage cloud-native AI services, Generative AI technologies, and advanced MLOps practices to build scalable, production-ready AI systems across the full AI lifecycle.

Responsibilities

• Design and develop AI and ML solutions using cloud-native AI and analytics services.
• Build and maintain scalable data pipelines for model training, deployment, monitoring, and production operations.
• Implement DevOps and MLOps practices to streamline model development, automation, and lifecycle management.
• Customize, fine-tune, and deploy Deep Learning, Generative AI, and Large Language Model solutions.
• Design AI solutions for cloud environments, edge devices, and High-Performance Computing infrastructures.
• Evaluate model performance and communicate solution effectiveness through measurable business outcomes and technical metrics.
• Conduct research and development on emerging AI technologies, algorithms, and advanced computational methods.
• Collaborate with cross-functional teams including architects, data engineers, software engineers, and business stakeholders to deliver scalable AI solutions.

Must haves

• 4-7 years of experience in Artificial Intelligence, Machine Learning, Data Science, Data Engineering, or related technical disciplines.
• Hands-on experience designing, developing, and deploying AI/ML applications in enterprise environments.
• Strong programming skills in Python and experience with AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or similar technologies.
• Experience with Deep Learning, Generative AI, Large Language Models, and modern AI development frameworks.
• Knowledge of cloud platforms such as Microsoft Azure, AWS, or Google Cloud and their AI/ML services.
• Experience building data pipelines and implementing MLOps practices for model deployment, monitoring, and optimization.

Nice to haves

• Experience developing and deploying Generative AI applications, foundation models, and LLM-based solutions.
• 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, Cloud Platforms, or related technologies.

We refresh listings regularly, but some roles close early on the source platform.