AI Sr Lead Engineer (AI ML)

at  Photon

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 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.

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.