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Syd Aweis

@sydaweis

Senior AI Engineer at Stafflink building production GenAI and RAG systems that support 500+ users and 8,000 daily requests.

United States

Message

At Stafflink, I architect production-grade GenAI applications using Python, LangChain, and LLM APIs, supporting 500+ users and 8,000 daily requests.

I engineered RAG pipelines with hybrid search, embeddings, and contextual re-ranking, improving answer relevance by 28%. I also developed LangGraph agent workflows that automated enterprise processes and saved 12 hours weekly.

At Blue Sheild, I developed LLM-powered applications and fine-tuned transformer models using Hugging Face Transformers, PyTorch, and PEFT. The fine-tuning improved task-specific model performance by 17% while reducing training resource requirements by 40%.

At Weights & Biases, I developed machine learning workflows for predictive modeling and classification, improving model performance by 18%. I also built reusable data-processing and model-development pipelines handling 1M+ records.

Experience

Work history, roles, and key accomplishments

Current

Senior AI Engineer

Current

Stafflink

Oct 2024 - Present (2 years 1 month)

Architected production-grade GenAI applications using Python, LangChain, and LLM APIs, supporting 500+ users and 8,000 daily requests. Engineered RAG pipelines and AI agent workflows, improving answer relevance by 28% and saving 12 hours weekly.

Python Lang Chain LLM APIs RAG Hybrid Search Embeddings Context Re Ranking LangGraph REST APIs Docker AWS CI CD Prompt Engineering Vector Databases Pandas

AI Engineer

Blue Sheild

Mar 2022 - Sep 2024 (2 years 6 months)

Developed and deployed LLM-powered applications combining transformer-based language models, structured knowledge, and semantic retrieval, supporting AI-powered business workflows for 300+ users. Engineered scalable Python pipelines and fine-tuned transformer models, improving response accuracy by 24% and reducing training resources by 40%.

Python LLM Transformers Hugging Face PyTorch PEFT Prompt Engineering Embedding Based Retrieval Model Evaluation Precision Recall F1 Score

Machine Learning Engineer

Weights & Biases

Aug 2019 - Feb 2022 (2 years 6 months)

Developed and optimized machine learning workflows for predictive modeling, classification, and automation, improving model performance by 18% through systematic experimentation and feature engineering. Built reusable Python pipelines handling 1M+ records and implemented model evaluation workflows across 20+ experiments.