Senior Machine Learning Engineer

1 week ago


Charlotte, United States Hirextra -World's First Staffing Aggregator Full time

AI-ML Platform Tech Lead & Arch

Location: Onsite – Charlotte, NC /Concord, CA

12+ Months


Tops skills required: AI/ML Platform Architecture, ML algorithms, Deep Learning Architecture, GCP/Azure, CI/CD


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.


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