MLOps Intern
Ve3
Posted on Feb 16, 2026
About Us
VE3 is a technology and business consultancy focused on delivering end-to-end technology solutions and products. We have successfully serviced enterprises across multiple markets, including the public and private sectors. Our services span all aspects of business, providing a holistic approach to managing an organization. We are committed to providing technical innovations and tools that empower organizations with critical information to facilitate decision-making that results in business transformation through cost savings and increased operational efficiency. Our commitment to quality is adopted throughout the organization and sets the foundation for delivering our full suite of capabilities.
Job Description
Job title: MLOps Intern
Requirements
What You'll Do:
• Work directly on a live client project developing time-series models geo science data
• Design, develop, and train time-series models to identify patterns, trends, and anomalies in continuous data streams
• Conduct model validation, back testing, and performance evaluation using appropriate time-series metrics
• Design and implement end-to-end MLOps pipelines for automated model training, versioning, deployment, and monitoring
• Deploy production-grade models using Docker, Kubernetes, and cloud ML services, ensuring scalability and reliability
• Implement monitoring and alerting mechanisms for model drift, data drift, and anomaly detection performance
• Optimize model performance for latency and real-time inference requirements
• Collaborate with the Technical Architect on infrastructure design, scalability planning, and cost optimization
• Document system architecture, model assumptions, experiments, and production workflows
Requirements:
• MTech / MSc in Machine Learning, Data Engineering, AI, or related field (current student or recent graduate)
• Strong Python skills and experience with ML frameworks (scikit-learn, PyTorch, or TensorFlow)
• Academic project experience with time-series data or ML pipelines
• Familiarity with MLOps concepts (model versioning, CI/CD, containerization)
• Bonus: Experience with time-series database or streaming data tools
What You'll Learn:
• Production-grade MLOps delivery for offshore wind sector
• Time-series forecasting at scale with real client data
• Cloud ML infrastructure architecture and deployment
• Agile delivery methodology for enterprise AI projects
Benefits
- Competitive salary and benefits package.
- Opportunities for professional development and certification.
- Flexible working arrangements and a collaborative team environment.