About the role
AI Engineer role based on the published job description. Key responsibilities and requirements were extracted directly from the posting for quick review.
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 to ensure high-quality datasets.
- 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).
Requirements
- Experience in AI/ML model development, AI/MLOps, and cloud-based deployment.
- Strong communication and interpersonal skills.
- Ability to manage multiple projects and deliverables simultaneously.