AI Engineer

About the Job

We are looking for talented AI Engineers!

Key Responsibilities

• Design, develop, and operationalize end-to-end AI & ML models across cloud environments.
• Implement advanced analytics, feature engineering, and model optimization for performance, scalability, and reliability.
• Build production-ready ML pipelines using Azure ML, GCP Vertex AI, and associated cloud services.
• Develop CI/CD and MLOps workflows using Docker, Git, and MLflow for automated training and deployment.
• Contribute to architectural decisions, ensure adherence to standards, and create robust, maintainable ML components.
• Conduct experiment design, model evaluation, benchmarking, and documentation.
• Collaborate with product owners, domain experts, solution architects, and cross-functional teams to translate requirements into scalable ML solutions.

Qualifications

Essential Skills:
Proficiency in Machine Learning, Deep Learning, Generative AI, and Statistical Modeling.
Experience deploying ML and GenAI solutions at scale using Azure ML, GCP Vertex AI, BigQuery, or comparable cloud platforms.
Strong proficiency in Python, PyTorch, TensorFlow, and libraries like Hugging Face Transformers, LangChain, LlamaIndex.

Additional Knowledge:
Familiarity with big-data processing tools such as Spark, Databricks, Dataflow, Azure Data Factory (good to have).
Experience with containerization (Docker), version control (Git), experiment tracking (MLflow).

Mathematical & Technical Understanding:
Strong understanding of applied mathematics: probability, optimization, linear algebra, advanced statistics.
Familiarity with time-series modeling, computer vision, deep learning architectures, or generative models (e.g., GANs, Diffusion Models, LLMs) is a plus.