AI & Machine Learning Consultant

Role Overview

As an AI & Machine Learning Consultant, you will design, develop, and implement Artificial Intelligence (AI) and Machine Learning (ML) solutions that help organizations unlock business value through advanced analytics and intelligent automation. You will work across the AI development lifecycle, leveraging cloud-based AI services, Generative AI technologies, and scalable data platforms to deliver innovative, production-ready solutions. This role combines technical expertise, problem-solving, and collaboration to accelerate AI adoption and drive business outcomes.

Key Responsibilities

• Design and develop AI and Machine Learning solutions using cloud-native AI platforms, services, and modern development frameworks.
• Build and maintain scalable data pipelines to support data ingestion, model training, deployment, monitoring, and production operations.
• Apply DevOps and MLOps practices to automate and optimize model development, deployment, versioning, and lifecycle management.
• Develop, customize, and deploy Deep Learning, Generative AI, and Large Language Model (LLM) solutions tailored to business requirements.
• Assess business needs, data availability, and infrastructure requirements to recommend and implement effective AI solutions.
• Support AI deployments across cloud environments, edge computing platforms, and High-Performance Computing (HPC) infrastructures where applicable.
• Conduct research and experimentation on emerging AI technologies, algorithms, simulation techniques, and advanced analytical methods.
• Work with large-scale structured and unstructured datasets, applying data cleansing, preprocessing, and feature engineering techniques to improve model performance.
• Design and maintain efficient data, model, and knowledge storage solutions that enable scalable AI applications and retrieval capabilities.
• Collaborate with data engineers, solution architects, and business stakeholders to design and deliver enterprise-grade AI solutions.
• Evaluate model performance and communicate solution quality, scalability, and business value through measurable outcomes.
• Ensure AI solutions adhere to security, governance, compliance, and Responsible AI standards.

Basic Qualifications

• 4-7 years of experience in Artificial Intelligence, Machine Learning, Data Science, Analytics, Data Engineering, or related technical disciplines.
• Hands-on experience developing, testing, and deploying AI/ML solutions in enterprise environments.
• Strong programming skills in Python and experience with machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, or equivalent technologies.
• Experience working with Deep Learning, Generative AI, Large Language Models (LLMs), and advanced analytics techniques.
• Knowledge of cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform and their AI/ML services.
• Experience building scalable data pipelines and supporting MLOps practices for model deployment and operations.
• Strong understanding of data preprocessing, feature engineering, model evaluation, and performance optimization methodologies.

Preferred Qualifications

• Experience developing and deploying Generative AI, LLM-based applications, and 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 production support processes.
• Strong analytical thinking, problem-solving, and stakeholder management skills.
• Relevant certifications in Artificial Intelligence, Machine Learning, Data Science, Data Engineering, or Cloud Technologies are preferred.