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الوظيفة What You'll Do : Lead Innovation: Drive teams of machine learning engineers to implement gr...
الوظيفة
What You'll Do :
Lead Innovation: Drive teams of machine learning engineers to implement groundbreaking AI and Generative AI solutions in large-scale enterprise environments.
Design the Future: Architect advanced cloud analytics platforms that span the entire data science lifecycle, with a focus on AIOps best practices.
Shape Strategy: Help our clients craft robust strategies and methodologies for leveraging data science and machine learning in cloud ecosystems.
Master Cloud Technologies: Work with leading tools and platforms like Azure Databricks, Azure Machine Learning, Amazon SageMaker, Google Vertex AI, and more to develop cutting-edge solutions.
Build Our Vision: Collaborate to define SDG’s value proposition in data science, particularly around next-gen architectures for machine learning systems.
Create Impact: Work closely with consulting and sales teams to craft compelling business proposals, bringing your solution architecture expertise to every project.
AI Systems Tech Architecture Solution Design: Designing technical architecture solutions for AI systems, leveraging frameworks and best practices from vendors or hyperscalers, or drawing on our extensive engineering experience, to create robust scalable AI/ML systems that ensure seamless integration and performance
AI Digital Twin Foundation: building a robust foundation with a composable architecture of AI and ML systems, rule-based systems, and cognitive knowledge chains enhanced by generative AI. This enables real-time monitoring, simulation, and optimization of virtual representations of physical systems for enhanced operational efficiency.
What We’re Looking For :
A degree in Computer Science, Telecommunications Engineering, or a related technical field with a strong background in software engineering.
8+ years of professional experience, with at least 5 years specializing as a machine learning engineer or machine learning architect.
Deep theoretical and practical expertise in data science fundamentals, solution lifecycles, and AIOps methodologies.
Strong background in software development and AI implementation.
Proven experience designing and building scalable architectures for machine learning platforms in the cloud.
Advanced knowledge of state-of-the-art cloud technologies and platforms for AI, including Azure, AWS, and Google Cloud.
Excellent communication and presentation skills, with the ability to explain complex concepts to both technical and non-technical audiences.
Preferred Qualifications :
A Master’s or PhD in Big Data, Artificial Intelligence, or related fields.
Strong understanding of data architectures and information modeling strategies.
Previous consulting experience in Data & Analytics.
Experience as a data engineer in analytics environments like data warehouses or data lakes.
Expertise in cloud-based data processing architectures and automation solutions.
Hands-on experience with Generative AI models, including Large Language Models (LLMs), neural networks, and recommendation systems.
Proficiency with tools and frameworks like TensorFlow, PyTorch, Hugging Face, and OpenAI.
Certifications in cloud platforms like AWS, Azure, or Google Cloud, with a focus on machine learning architecture.
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