What are the responsibilities and job description for the AI-ML Platform Tech Lead & Arch position at Resource Informatics Group, Inc?
AI-Client Platform Tech Lead & Arch
Location: Concord, CA/SFO/ Charlotte NC
Key Responsibilities:
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.
- 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.
