AI Team Lead

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).