What are the responsibilities and job description for the AIML Architect position at AIT Global inc.?
Job Title: AIML Architect
Location: Charlotte, NC & San Leandro, CA
Location: Charlotte, NC & San Leandro, CA
Key Responsibilities:
- Design and architect scalable AI platforms to develop, deploy AI solutions leveraging ML 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/ML architecture best practices, frameworks, and standards.
- Lead AI/ML infrastructure setup, including cloud services selection, data pipelines, and model deployment.
- Ensure robustness, reliability, and scalability of AI/ML solutions in production environments.
- Design and implement data governance, security, and compliance measures for AI/ML platforms.
- Optimize AI/ML workflows for performance, cost efficiency, and resource utilization.
- Provide technical leadership and mentorship to AI/ML development teams.
- Communicate AI/ML architecture decisions and strategies to stakeholders and executives.
Key Requirements:
- Proven experience as an AI/ML platform architect
- Deep understanding of ML 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/ML models.
- Ability to design and optimize distributed computing systems for AI/ML workloads.
- Familiarity with DevOps practices, CI/CD pipelines, and automation tools in AI-ML contexts.
- Excellent problem-solving skills and ability to address complex technical challenges.
- Effective communication skills to collaborate with cross-functional teams and stakeholders.
