AI-ML Platform Tech Lead & Arch - Resource Informatics Group
Concord, CA
About the Job
AI-Client Platform Tech Lead & Arch
Location: Concord, CA/SFO/ Charlotte NC
Key Responsibilities:
· Design and architect scalable AI platforms to develop, deploy AI solutions leveraging Client techniques and Deep Learning Techniques.
· Drive Joint Architecture Design to collaborating with business stakeholders, data scientists, engineering teams, product, and other key partners to gather functional, non-functional requirements for solving AI use case on the AI Platform
· Evaluate emerging technologies and tools in AI area and do fitment analysis to the Enterprise AI Platform and capabilities strategy.
· Define and implement AI/Client architecture best practices, frameworks, and standards.
· Lead AI/Client infrastructure setup, including cloud services selection, data pipelines, and model deployment.
· Ensure robustness, reliability, and scalability of AI/Client solutions in production environments.
· Design and implement data governance, security, and compliance measures for AI/Client platforms.
· Optimize AI/Client workflows for performance, cost efficiency, and resource utilization.
· Provide technical leadership and mentorship to AI/Client development teams.
· Communicate AI/Client architecture decisions and strategies to stakeholders and executives.
Key Requirements:
· Proven experience as an AI/Client platform architect
· Deep understanding of Client algorithms, Deep Learning architechture, models, and frameworks (e.g., TensorFlow, PyTorch, Scikit-Learn).
· Expertise in cloud platforms (e.g., GCP, Azure) and their AI services.
· Strong knowledge of Model development life cycle, software engineering principles, data engineering principles
· Experience with containerization and orchestration tools onprem and cloud (e.g., AKS, GKE, OpenShift Container Platform, Docker, Kubernetes) for deploying AI/Client models.
· Ability to design and optimize distributed computing systems for AI/Client workloads.
· Familiarity with DevOps practices, CI/CD pipelines, and automation tools in AI-Client contexts.
· Excellent problem-solving skills and ability to address complex technical challenges.
· Effective communication skills to collaborate with cross-functional teams and stakeholders.
Location: Concord, CA/SFO/ Charlotte NC
Key Responsibilities:
· Design and architect scalable AI platforms to develop, deploy AI solutions leveraging Client techniques and Deep Learning Techniques.
· Drive Joint Architecture Design to collaborating with business stakeholders, data scientists, engineering teams, product, and other key partners to gather functional, non-functional requirements for solving AI use case on the AI Platform
· Evaluate emerging technologies and tools in AI area and do fitment analysis to the Enterprise AI Platform and capabilities strategy.
· Define and implement AI/Client architecture best practices, frameworks, and standards.
· Lead AI/Client infrastructure setup, including cloud services selection, data pipelines, and model deployment.
· Ensure robustness, reliability, and scalability of AI/Client solutions in production environments.
· Design and implement data governance, security, and compliance measures for AI/Client platforms.
· Optimize AI/Client workflows for performance, cost efficiency, and resource utilization.
· Provide technical leadership and mentorship to AI/Client development teams.
· Communicate AI/Client architecture decisions and strategies to stakeholders and executives.
Key Requirements:
· Proven experience as an AI/Client platform architect
· Deep understanding of Client algorithms, Deep Learning architechture, models, and frameworks (e.g., TensorFlow, PyTorch, Scikit-Learn).
· Expertise in cloud platforms (e.g., GCP, Azure) and their AI services.
· Strong knowledge of Model development life cycle, software engineering principles, data engineering principles
· Experience with containerization and orchestration tools onprem and cloud (e.g., AKS, GKE, OpenShift Container Platform, Docker, Kubernetes) for deploying AI/Client models.
· Ability to design and optimize distributed computing systems for AI/Client workloads.
· Familiarity with DevOps practices, CI/CD pipelines, and automation tools in AI-Client contexts.
· Excellent problem-solving skills and ability to address complex technical challenges.
· Effective communication skills to collaborate with cross-functional teams and stakeholders.
Source : Resource Informatics Group
