AI-ML Tech Lead/Architect – NC, USA Full-time

Job Description

Greetings Everyone

Who are we?

For the past 20 years, we have powered many Digital Experiences for the Fortune 500. Since 1999, we have grown from a few people to more than 4000 team members across the globe that are engaged in various Digital Modernization. For a brief 1 minute video about us, you can check https://youtu.be/uJWBWQZEA6o.

What will you do? What are we looking for?

Job Requisition for AI-ML Platform Tech Lead & Arch

Location: Charlotte NC

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.

What will make people successful in the team:

• Superior tech skills with coding to design to presentation
• On the feet thinking
• Outstanding communication skills
• 15 day rampup time