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AI Solutions Architect

2 months ago

Charlotte, North Carolina, United States Micasa Global Full time

Primary Responsibilities:

  • Architect and design robust AI frameworks to create and implement AI solutions utilizing machine learning methodologies and advanced neural network techniques.
  • Facilitate collaborative architecture design sessions with business partners, data analysts, engineering teams, product managers, and other essential stakeholders to collect both functional and non-functional requirements for addressing AI use cases on the AI platform.
  • Assess and analyze new technologies and tools within the AI domain to determine their compatibility with the Enterprise AI platform and strategic capabilities.
  • Establish and enforce best practices, frameworks, and standards for AI/ML architecture.
  • Oversee the setup of AI/ML infrastructure, including the selection of cloud services, data processing pipelines, and model deployment strategies.
  • Guarantee the robustness, dependability, and scalability of AI/ML solutions in operational settings.
  • Design and implement measures for data governance, security, and compliance within AI/ML platforms.
  • Enhance AI/ML workflows for optimal performance, cost-effectiveness, and resource management.
  • Provide technical guidance and mentorship to AI/ML development teams.
  • Articulate AI/ML architectural decisions and strategies to stakeholders and executive leadership.

Essential Qualifications:

  • Demonstrated experience as an architect for AI/ML platforms.
  • In-depth knowledge of machine learning algorithms, deep learning architectures, models, and frameworks (such as TensorFlow, PyTorch, Scikit-Learn).
  • Proficiency in cloud computing platforms (like Google Cloud Platform, Azure) and their associated AI services.
  • Strong understanding of the model development lifecycle, software engineering principles, and data engineering practices.
  • Experience with containerization and orchestration technologies both on-premises and in the cloud (including AKS, GKE, OpenShift Container Platform, Docker, Kubernetes) for deploying AI/ML models.
  • Capability to design and optimize distributed computing systems tailored for AI/ML workloads.
  • Familiarity with DevOps methodologies, CI/CD pipelines, and automation tools in the context of AI/ML.
  • Exceptional problem-solving abilities to tackle intricate technical challenges.
  • Strong communication skills to effectively collaborate with cross-functional teams and stakeholders.