About the role
AI summarisedWe are seeking an experienced AI Engineer to architect, build, and maintain end-to-end AI/ML pipelines. This role involves operationalizing experimental models into production environments, implementing MLOps practices, and integrating AI solutions into enterprise systems using cloud-native services.
IndustrialOnsite
Key Responsibilities
- Architect, build, and maintain end-to-end AI/ML pipelines (data ingestion, preprocessing, training, deployment, predictive analytics / monitoring).
- Collaborate with data scientists and domain experts to operationalize experimental models, optimizing for performance, scalability, and latency.
- Implement and advocate for AI/MLOps practices (CI/CD for ML, model versioning, feature stores) using modern tools.
- Optimize model inference for production environments (e.g., using TensorRT, ONNX, pruning, quantization).
- Write robust, testable, and maintainable code in a collaborative setting using GitHub.
- Integrate AI models into enterprise systems using APIs and cloud-native services (AWS, Azure).
- Ensure models meet business objectives while adhering to ethical AI and governance frameworks.
- Provide technical support and training to users, troubleshoot system issues, and document processes.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related quantitative field.
- Minimum of 5-7 years of professional experience in AI/ML model development and deployment.
- At least 3-4 years focused on building and deploying machine learning models and AI solutions in a production environment.
- Proven track record of taking AI/ML projects from concept to deployment and monitoring.
- Excellent analytical and problem-solving abilities.
- Strong communication and interpersonal skills.
- Ability to manage multiple projects and deliverables simultaneously.