About the role
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).
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