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Vetted Text Summarization Professionals
Pre-screened and vetted.
Senior AI/ML Engineer specializing in NLP, LLMs, and retrieval systems
Senior Machine Learning Engineer specializing in recommender systems, search, and NLP/GenAI
Kaiqi Zhang
Senior Full-Stack Engineer specializing in cloud-native SaaS and AI applications
“ML/LLM engineer with hands-on experience shipping production RAG systems at Google Clinical Search and GenAI recommendation/summarization features in Meta Ads. Stands out for combining research-to-production execution with rigorous grounding, evaluation, safety checks, and reusable Python platform components that improved both reliability and team velocity.”
Senior AI/ML Engineer specializing in LLMs, recommendation systems, and ML platforms
Christopher Sipola
Senior Machine Learning Engineer specializing in LLMs and recommendation systems
“ML/GenAI engineer who owned major parts of Spotify’s AI DJ from offline experimentation through deployment, monitoring, and iteration. They combine recommender systems, RAG, real-time feedback loops, and LLM safety/orchestration to ship consumer-facing personalization features that drove double-digit engagement and deeper listening sessions.”
Senior AI/ML Engineer specializing in LLMs, RAG, and multimodal systems
Senior AI/ML Engineer specializing in Generative AI, RAG, and MLOps for FinTech
Senior AI/ML Engineer specializing in conversational AI and enterprise LLM systems
Senior Software Engineer specializing in AI/ML and customer-facing platforms
Mid-level Data Scientist specializing in Generative AI and LLM applications
Brian Gomez
Senior Machine Learning Engineer specializing in AI/ML, NLP, and computer vision
“McKinsey & Company ML/NLP practitioner who builds production-grade AI systems across sectors (notably healthcare and finance), including RAG/LLM solutions, entity resolution pipelines, and embedding-powered search with vector databases. Demonstrated measurable impact (40% reduction in data duplication) and strong MLOps/data workflow practices (Airflow, MLflow, Spark, AWS/GCP, Prometheus, CI/CD).”
Deepak Guntreddi
Mid-level Full-Stack Developer specializing in Java/Spring Boot and React
“NVIDIA engineer who built and shipped a production LLM-powered enterprise knowledge system (summarization, transcription, and Q&A) that cut document retrieval time ~30%. Deep hands-on experience with RAG (FAISS/Pinecone), GPU-accelerated microservices on AWS, and reliability/safety practices (Guardrails AI, prompt A/B testing, canary releases) plus strong MLOps orchestration across Airflow, Step Functions, and Kubernetes GitOps.”
Mid-level AI/ML Engineer specializing in LLMs, NLP, and MLOps
Mid-level Data Scientist / GenAI & ML Engineer specializing in LLM apps and MLOps
Mid-level Software Engineer specializing in backend APIs, data pipelines, and cloud microservices
Mid-level AI/ML Engineer specializing in LLMs, multilingual NLP, and low-latency MLOps
Mid-level Machine Learning Engineer specializing in Generative AI and LLM applications
Subhash Mothukuru
Mid-level Machine Learning Engineer specializing in LLMs, generative AI, and MLOps
“Built and shipped a production LLM-powered medical scribe that generates structured clinical visit summaries using RAG, strict JSON schemas, and post-generation validation to reduce hallucinations. Experienced in making LLM workflows deterministic and observable (structured logging/metrics/tracing) and in evaluation-driven iteration with metrics like schema pass rate and edit rate; collaborated closely with clinicians and policy stakeholders at Scale AI to drive adoption.”