AI Team Lead

BlackStone eIT

. Lead the AI team in designing, developing, and implementing AI models and systems .

Posted 10/22/2026full-timeAmman • JordanSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading AI teams to design and implement advanced AI models, leveraging deep learning frameworks and cloud technologies. Proficient in managing the full project lifecycle while fostering innovation and best practices in machine learning.

Highest-signal resume keywords

Machine LearningDeep LearningPython ProgrammingTechnical LeadershipMicrosoft Azure

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningDeep LearningNLP ArchitecturesImage ProcessingCI/CD PipelinesModel DeploymentCustom Model BuildingModel MonitoringContainer OrchestrationMathematical Foundation

Soft Skills

CollaborationMentoringContinuous ImprovementInnovation

Tools & Technologies

PyTorchTensorFlowAzure MLMLflowDockerKubernetesHugging FaceLang ChainOpenCVTensorRT

Industry Keywords

AI EngineeringAutonomous AI AgentsEdge DeploymentComputer VisionModel Drift

Tech Stack

Tools & technologies

AzureDockerKubernetesPythonPyTorchTensorflow

About the role

Key responsibilities & impact

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 the project lifecycle from research and prototyping to production deployment
Maintain knowledge of the latest trends and advancements in AI and machine learning
Establish best practices and foster a culture of continuous improvement and innovation

Requirements

What you’ll need

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
Expert-level proficiency in Python and deep learning frameworks (PyTorch is strongly preferred, or TensorFlow)
Extensive, hands-on experience with Microsoft Azure, specifically building training and deployment pipelines using Azure ML workspace, MLflow, and container orchestration (Docker/Kubernetes)
Deep understanding of modern NLP architectures (Transformers, BERT, GPT variants), tokenization, vector databases, and libraries like Hugging Face and Lang Chain/Lang Graph
Strong mathematical foundation in image processing and experience building custom models using OpenCV, YOLO architectures, and PyTorch Vision
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)

Benefits

Comp & perks

Paid Time Off
Performance Bonus
Training & Development