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I am a results-driven AI Engineer & Data Scientist with 10+ years of experience architecting and scaling advanced ML, DL, NLP, CV, and GenAI solutions. I specialize in production-grade AI systems, leveraging models like GPT-4, Claude 3, Gemini 1.5, LLaMA 3, Mistral, Mixtral, and more. My work spans Retrieval-Augmented Generation, multi-agent systems, and custom fine-tuning across cloud-native and hybrid enterprise environments. I am proficient in Python and Golang, and experienced with LangChain, LlamaIndex, Transformers, FastAPI, PyTorch Lightning, and NVIDIA NeMo; I’ve designed and deployed scalable ML/GenAI solutions on AWS, GCP, and Azure, integrating function calling, tool-use, and multimodal inference across text, images, and audio. I am known for collaborating across teams, mentoring engineers, and aligning AI initiatives with business goals. My approach emphasizes responsible, explainable AI, robust MLOps, and advanced prompt engineering with retrieval fusion, context compression, and memory management. I stay engaged with emerging topics from synthetic data and LLM caching to edge AI inference, and I build observability, reliability, and governance into production systems.…I am a results-driven AI Engineer & Data Scientist with 10+ years of experience architecting and scaling advanced ML, DL, NLP, CV, and GenAI solutions. I specialize in production-grade AI systems, leveraging models like GPT-4, Claude 3, Gemini 1.5, LLaMA 3, Mistral, Mixtral, and more. My work spans Retrieval-Augmented Generation, multi-agent systems, and custom fine-tuning across cloud-native and hybrid enterprise environments. I am proficient in Python and Golang, and experienced with LangChain, LlamaIndex, Transformers, FastAPI, PyTorch Lightning, and NVIDIA NeMo; I’ve designed and deployed scalable ML/GenAI solutions on AWS, GCP, and Azure, integrating function calling, tool-use, and multimodal inference across text, images, and audio. I am known for collaborating across teams, mentoring engineers, and aligning AI initiatives with business goals. My approach emphasizes responsible, explainable AI, robust MLOps, and advanced prompt engineering with retrieval fusion, context compression, and memory management. I stay engaged with emerging topics from synthetic data and LLM caching to edge AI inference, and I build observability, reliability, and governance into production systems.

Ronny Powers

AI Engineer, Data Scientist, AI Developer, +1

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I am a results-driven AI Engineer & Data Scientist with 10+ years of experience architecting and scaling advanced ML, DL, NLP, CV, and GenAI solutions. I specialize in production-grade AI systems, leveraging models like GPT-4, Claude 3, Gemini 1.5, LLaMA 3, Mistral, Mixtral, and more. My work spans Retrieval-Augmented Generation, multi-agent systems, and custom fine-tuning across cloud-native and hybrid enterprise environments. I am proficient in Python and Golang, and experienced with LangChain, LlamaIndex, Transformers, FastAPI, PyTorch Lightning, and NVIDIA NeMo; I’ve designed and deployed scalable ML/GenAI solutions on AWS, GCP, and Azure, integrating function calling, tool-use, and multimodal inference across text, images, and audio. I am known for collaborating across teams, mentoring engineers, and aligning AI initiatives with business goals. My approach emphasizes responsible, explainable AI, robust MLOps, and advanced prompt engineering with retrieval fusion, context compression, and memory management. I stay engaged with emerging topics from synthetic data and LLM caching to edge AI inference, and I build observability, reliability, and governance into production systems.…I am a results-driven AI Engineer & Data Scientist with 10+ years of experience architecting and scaling advanced ML, DL, NLP, CV, and GenAI solutions. I specialize in production-grade AI systems, leveraging models like GPT-4, Claude 3, Gemini 1.5, LLaMA 3, Mistral, Mixtral, and more. My work spans Retrieval-Augmented Generation, multi-agent systems, and custom fine-tuning across cloud-native and hybrid enterprise environments. I am proficient in Python and Golang, and experienced with LangChain, LlamaIndex, Transformers, FastAPI, PyTorch Lightning, and NVIDIA NeMo; I’ve designed and deployed scalable ML/GenAI solutions on AWS, GCP, and Azure, integrating function calling, tool-use, and multimodal inference across text, images, and audio. I am known for collaborating across teams, mentoring engineers, and aligning AI initiatives with business goals. My approach emphasizes responsible, explainable AI, robust MLOps, and advanced prompt engineering with retrieval fusion, context compression, and memory management. I stay engaged with emerging topics from synthetic data and LLM caching to edge AI inference, and I build observability, reliability, and governance into production systems.

Available to hire

I am a results-driven AI Engineer & Data Scientist with 10+ years of experience architecting and scaling advanced ML, DL, NLP, CV, and GenAI solutions. I specialize in production-grade AI systems, leveraging models like GPT-4, Claude 3, Gemini 1.5, LLaMA 3, Mistral, Mixtral, and more. My work spans Retrieval-Augmented Generation, multi-agent systems, and custom fine-tuning across cloud-native and hybrid enterprise environments. I am proficient in Python and Golang, and experienced with LangChain, LlamaIndex, Transformers, FastAPI, PyTorch Lightning, and NVIDIA NeMo; I’ve designed and deployed scalable ML/GenAI solutions on AWS, GCP, and Azure, integrating function calling, tool-use, and multimodal inference across text, images, and audio.

I am known for collaborating across teams, mentoring engineers, and aligning AI initiatives with business goals. My approach emphasizes responsible, explainable AI, robust MLOps, and advanced prompt engineering with retrieval fusion, context compression, and memory management. I stay engaged with emerging topics from synthetic data and LLM caching to edge AI inference, and I build observability, reliability, and governance into production systems.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Work Experience

AI / ML Engineer at Adept AI

October 1, 2023 - December 1, 2025

Designed and automated end-to-end testing frameworks using Playwright, integrated into CI/CD pipelines (GitHub Actions and Jenkins) for automated regression testing across environments; implemented cross-browser testing strategies and trace-based debugging to accelerate release cycles. Architected scalable GenAI/ML platforms, including multi-agent LLM workflows with LangChain and CrewAI, RAG and GraphRAG retrieval using Neo4j and vector stores, and low-latency embeddings optimization. Built and deployed enterprise-grade Copilot agents with Microsoft Copilot Studio, Semantic Indexing, and SharePoint data sources; implemented security, multi-tenant governance, and observability using Prometheus, OpenTelemetry, and DataDog. Led containerized deployments on Kubernetes with Terraform, and established MLOps pipelines (MLflow, wandb, BentoML, KServe) for model training, validation, and serving. Mentored engineers across product, sales, and customer teams to translate ambiguous business proble

AI / ML Engineer / Data Engineer at Snorkel AI

May 1, 2020 - September 1, 2023

Directed end-to-end automation for a multi-tenant enterprise dashboard; built modular Playwright test suites supporting role-based workflows; created fixtures and shared utilities to standardize test logic across complex UI components. Implemented production-grade data pipelines, GIS/spatial data conflation, and graph-based knowledge graphs with Neo4j. Delivered Palantir Foundry deployments for scalable data workflows; designed GenAI demos and pilot implementations; implemented Retrieval-Augmented Generation (RAG) and GraphRAG retrieval; optimized vector search across Pinecone and FAISS. Ensured HIPAA/GDPR governance, delivered real-time fraud detection pipelines via SageMaker Pipelines and Lambda, and containerized ML services for scalable serving.

MLOps & Machine Learning Platform Engineer at DataRobot

November 1, 2015 - April 1, 2020

Designed and deployed AI-driven credit risk models; automated legal document summarization workflows; built advanced customer segmentation and sentiment analysis pipelines. Scaled production ML workloads with Kubernetes autoscaling; processed large-scale data with PySpark; engineered ETL/ELT pipelines with Databricks; automated ML infrastructure with Databricks Jobs; integrated Azure Cognitive Search; trained large TensorFlow models with custom multi-head attention; developed OCR/NLP pipelines, containerized NLP models for Kubernetes deployment, and served real-time and batch inferences via SageMaker Endpoints; modernized monoliths into microservices and implemented GPU-accelerated vision pipelines.