Immediate Opening For an AI Engineer

Key Responsibilities

• Design and implement end-to-end AI/ML solutions from data ingestion to deployment.
• Build and optimize machine learning and deep learning models for real-world applications.
• Architect scalable and secure AI systems using cloud platforms.
• Work on Generative AI use cases including LLMs, prompt engineering, and fine-tuning.
• Collaborate with cross-functional teams to translate business requirements into AI solutions.
• Develop and manage data pipelines and model lifecycle (MLOps).
• Ensure model performance, scalability, reliability, and monitoring in production.
• Stay updated with emerging AI trends and evaluate new tools/technologies.
• Mentor junior engineers and guide best practices in AI development.

Required Skills

• Strong proficiency in Python and AI/ML libraries (TensorFlow, PyTorch, Scikit-learn).
• Experience with Machine Learning, Deep Learning, and NLP.
• Hands-on experience with Generative AI (LLMs, embeddings, prompt engineering).
• Knowledge of MLOps tools (MLflow, Kubeflow, Azure ML, etc.).
• Knowledge of cloud platforms (Azure, AWS, or GCP).
• Understanding of data engineering concepts and working with large datasets.
• Familiarity with APIs, microservices, and containerization (Docker, Kubernetes).
• Strong problem-solving and analytical skills.

Nice to Have

• Certifications in AI/ML or cloud platforms.
• Experience working on production-grade AI systems.
• Contributions to open-source AI projects.
• Azure Foundry and Databricks Agent bricks are good to have