BlackStone eIT is actively looking for a dedicated AI Team Lead to spearhead our Artificial Intelligence initiatives. This role involves leading a talented team of AI professionals to create innovative AI-driven solutions that align with the company's vision. You will play a crucial part in strategizing, developing, and deploying AI technologies that enhance our products and services while maintaining the highest standards of excellence.

Responsibilities:

• Lead the AI team in designing, developing, and implementing AI models and systems.
• Collaborate with stakeholders to identify AI opportunities that drive business value.
• Guide the team to effectively use machine learning frameworks and tools.
• Oversee project lifecycle from research and prototyping to production deployment.
• Maintain knowledge of latest trends and advancements in AI and machine learning.
• Establish best practices and foster a culture of continuous improvement and innovation.

Requirements

• Experience: 6+ years of hands-on experience in Machine Learning, Deep Learning, or AI Engineering.
• 3+ years of experience in a technical leadership or mentoring role.
• Programming & Frameworks: Expert-level proficiency in Python and deep learning frameworks (PyTorch is strongly preferred, or TensorFlow).
• Cloud Infrastructure: Extensive, hands-on experience with Microsoft Azure, specifically building training and deployment pipelines using Azure ML workspace, MLflow, and container orchestration (Docker/Kubernetes).
• NLP Expertise: Deep understanding of modern NLP architectures (Transformers, BERT, GPT variants), tokenization, vector databases, and libraries like Hugging Face and Lang Chain/Lang Graph.
• CV Expertise: Strong mathematical foundation in image processing and experience building custom models using OpenCV, YOLO architectures, and PyTorch Vision.
• MLOps: Proven ability to build CI/CD pipelines for machine learning models, manage model registries, and monitor model drift in production.
• Experience with building and deploying Autonomous AI Agents (e.g., using Langchain,langgraph,Crew ai ).
• Background in edge deployment for Computer Vision models (TensorRT, ONNX).