The AI Engineer will design, develop, and deploy machine learning models to address complex challenges. This role requires collaboration with Data Scientists and Software Engineers to integrate AI features into core products. The ideal candidate will have experience in model development, data engineering, and optimization of machine learning systems. Familiarity with various AI architectures is an advantage.
Key Responsibilities
Model Development: Design and implement machine learning and deep learning models (NLP, Computer Vision, or Predictive Analytics).
Data Engineering: Build scalable data pipelines to ingest, clean, and preprocess large datasets for training.
Deployment: Use tools like Docker and Kubernetes to move models from research to production-ready APIs.
Optimization: Fine-tune model performance and monitor system health to ensure high reliability and low latency.
Collaboration: Work closely with Data Scientists and Software Engineers to integrate AI features into our core products.
Required Skills
Programming: Proficiency in Python (PyTorch, TensorFlow, or JAX).
Mathematics: Strong grasp of linear algebra, calculus, and statistics.
Infrastructure: Experience with cloud platforms (AWS, GCP, or Azure) and MLOps workflows.
Architectures: Familiarity with Transformers, CNNs, or LLM fine-tuning techniques.