Principal Architect - AI/ML
New
Z
ZencoreCloud Computing AI/ML
USAFull-TimePrincipal
Salary not disclosed
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Job Details
- Required Skills
- GCPMachine LearningPyTorchLangChain
Requirements
- Master’s degree in Computer Science, natural sciences, mathematics, or related technical field, or equivalent practical experience.
- Extensive experience in a senior or principal architect role with a track record of delivering production-grade machine learning systems.
- Deep, hands-on architectural experience with at least one major cloud platform (GCP, AWS, or Azure).
- Proven expertise in LLM optimization techniques such as quantization, pruning, and efficient fine-tuning (e.g., LoRA).
- Direct experience with high-performance serving frameworks (e.g., vLLM, TensorRT-LLM).
- Hands-on experience with high-performance ML frameworks (e.g., JAX, PyTorch/XLA).
- Expertise in designing and deploying agentic workflows using code-centric (LangGraph, LangChain, Google ADK) or low-code paradigms.
- Experience with LLM observability and evaluation frameworks (e.g., LangSmith, LangFuse, Vertex AI Evaluation).
- Strong understanding of architectural patterns for secure, private, and data-sovereign AI.
- Exceptional communication and stakeholder management skills.
Responsibilities
- Serve as Zencore’s senior-most technical authority on the practical application of advanced artificial intelligence and machine learning.
- Partner with the sales and business development teams in a pre-sales capacity to scope opportunities and design solutions.
- Lead the architecture and design of sophisticated, secure, and scalable AI solutions for clients.
- Collaborate with Cloud & Data Architects to guarantee the design and deployment of comprehensive client solutions.
- Design systems that meet strict GDPR and data privacy requirements while ensuring model explainability.
- Architect solutions for hosting, fine-tuning, and optimizing proprietary and open-source models on hyperscaler platforms.
- Guide and mentor customers and engineering teams on high-performance training, model serving, and agentic systems.
- Perform ROI analysis and cost-optimization strategies for large-scale AI deployments.
- Act as an external thought leader through blog posts, conference presentations, and community engagement.
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