Machine Learning Engineer

Requirements:

• 3-5 years of hands-on experience designing and implementing cloud solutions on Azure (preferred) and/or AWS.
• Expertise in Python for backend services, automation, and API development.
• Strong understanding of cloud concepts: IaaS, PaaS, SaaS, serverless computing, and cloud-native architectures.
• Hands-on experience with: Azure App Services, Functions, App Insights, API Management, AWS Lambda, ECS/EKS, S3 CloudWatch (if applicable).
• Terraform, ARM Templates, Ansible, MLflow or equivalent ML lifecycle management tools, Docker and Kubernetes / AKS.
• Experience building CI/CD pipelines using Jenkins (Groovy scripts), Azure DevOps, or GitHub Actions.
• Deep knowledge of networking, security, identity, monitoring, and cost optimisation in cloud environments.
• Experience implementing scalable production-grade systems for AI/ML workloads is a strong plus.

Consulting Experience:

• Proven track record in an IT consulting environment, engaging with large enterprises and MNCs in strategic data solutioning projects.
• Strong stakeholder management, business needs assessment, and change management skills.

Leadership and Soft Skills:

• Experience managing and mentoring small teams, developing technical skills in AI domains.
• Ability to influence and align cross-functional teams and stakeholders.
• Excellent communication, documentation, and presentation skills.
• Strong problem-solving, analytical thinking, and strategic vision.

Skills

AWS, Ansible, Azure, Azure DevOps, Docker, GitHub Actions, Jenkins, Kubernetes, MLflow, Python, Terraform