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What you’ll do
AI Strategy Development: Define and drive the organization's AI strategy, identifying opportunities for AI adoption to enhance business processes, improve decision-making, and achieve competitive advantage.
AI Architecture Design: Senior Developer and design scalable, reliable, and efficient AI systems and infrastructure that support the development, deployment, and maintenance of AI solutions.
AI Solution Design: Collaborate with data scientists, software engineers, and domain experts to design end-to-end AI solutions that align with business requirements, ensuring scalability, performance, and maintainability.
Data Architecture: Define the data architecture, data pipelines, and data integration strategies required to support AI initiatives, including data ingestion, storage, transformation, and retrieval.
Model Selection and Evaluation: Guide the selection and evaluation of machine learning and deep learning models, ensuring they are aligned with business goals and meet performance, accuracy, and interpretability requirements.
Infrastructure Planning: Collaborate with IT teams to define the infrastructure requirements for AI solutions, including hardware, cloud services, and deployment frameworks.
Security and Compliance: Ensure AI solutions adhere to security and privacy standards, as well as regulatory compliance requirements, considering aspects such as data protection, confidentiality, and ethical considerations.
Industry Knowledge and Innovation: Stay abreast of the latest trends, advancements, and best practices in AI, actively seeking opportunities to drive innovation and introduce new AI capabilities to the organization.
What you bring
Bachelor's or master's degree in computer science, data science, or a related field. A Ph.D. in a relevant discipline is a plus.
8+ years of extensive experience in designing and architecting AI solutions, with a strong understanding of machine learning, deep learning, and data analytics techniques.
Proven track record of successfully leading and delivering large-scale AI projects, from conception to deployment.
Strong knowledge of AI frameworks, libraries, and tools, such as TensorFlow, PyTorch, scikit-learn, and cloud-based AI services.
Expertise in data architecture, including data modeling, data integration, and data governance principles.
Familiarity with big data technologies, such as Hadoop, Spark, and distributed computing frameworks.
Experience with cloud platforms and services, such as AWS, Azure, or Google Cloud, for scalable and reliable AI infrastructure.
Understanding of software engineering principles, DevOps practices, and agile methodologies.
Strong analytical and problem-solving abilities, with the capability to assess complex business requirements and translate them into AI solutions.
Demonstrated ability to stay up to date with the latest AI research, trends, and industry advancements.
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