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Position: Validation Framework – Development, Maintenance, Testing (BB48FT RM 3802)
Essential duties and responsibilities:
Design and implement efficient AI inference pipelines for production environments
Optimize model serving architecture for low-latency, high-throughput inference
Develop and maintain inference operations infrastructure and monitoring systems
Establish comprehensive metrics and monitoring for AI model performance
Develop frameworks for measuring latency, throughput, accuracy, and resource utilization
Conduct performance profiling and bottleneck analysis
Build reusable Python modules and frameworks for ML operations
Develop C wrapper libraries for performance-critical components
Create APIs and SDKs for model deployment and inference
Containerize ML models and services using Docker
Design multi-stage Docker builds for optimized container images
Implement orchestration solutions (Kubernetes, Docker Compose)
Manage container registries and deployment pipelines
Integrate vector databases with AI applications (RAG, semantic search, recommendation systems)
Qualifications:
Deep understanding of machine learning concepts, model architectures, and inference optimization
Experience with MLflow, Kubeflow, or similar ML platform tools
Hands-on experience with vector databases (Pinecone, Weaviate, Milvus, Qdrant, ChromaDB, or similar)
Strong proficiency in Python; experience with C/C++ for wrapper development
Proficient in Docker, container optimization, and orchestration platforms
PREFERRED:
Experience with LLM frameworks (LangChain, LlamaIndex, Hugging Face)
Experience with streaming inference and real-time systems
Knowledge of PCIe Gen4/5/6 technology is an advantage
Previous experience with storage systems, protocols, and NAND flash is an advantage
SKILLS:
Excellent interpersonal skills
Strong can-do attitude
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