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Vetted Databricks Professionals
Pre-screened and vetted.
Mid-level Data Analyst / BI Analyst specializing in analytics, governance, and dashboards
Senior Full-Stack AI/ML Engineer specializing in cloud data platforms and GenAI
Senior Full-Stack Engineer specializing in AI-powered SaaS and cloud-native analytics
Principal Data Scientist specializing in ML, NLP, and forecasting for marketing and supply chain
Principal Machine Learning Scientist specializing in GenAI, LLMs, and RAG
Engineering leader specializing in data platforms and distributed systems
Intern Embedded/Systems Software Engineer specializing in firmware and RTOS
Senior Full-Stack Engineer specializing in cloud, real-time data, and web platforms
Senior Software Engineer specializing in cloud platforms, healthcare imaging, and scalable APIs
Senior Full-Stack Software Engineer specializing in Telehealth and FinTech
Director-level Product-Led CTO specializing in AI/MarTech, retail media, and omnichannel platforms
Senior Full-Stack Software Engineer specializing in large-scale streaming platforms
Mid-level Machine Learning Engineer specializing in generative AI, NLP, and MLOps
Sumer Joshi
Senior Backend Software Engineer specializing in healthcare platforms and AI/ML tooling
“Built a chatbot for a learning management system during a Deep Atlas bootcamp by mapping an end-to-end RAG architecture (document ingestion, Qdrant-based retrieval scoring, and LLM response synthesis). Previously at Rally Health/UnitedHealthcare, diagnosed load-related memory spikes with JMeter and improved stability by migrating caching from Guava to Redis, and also supported adoption through UI A/B testing in a technical marketing engineer rotation.”
Krishna Sahith Poruri
Mid-level AI/ML Engineer specializing in LLMs, RAG, and MLOps
“ML/LLM engineer who built a production RAG system (GPT-4 + FAISS + FastAPI) to deliver fast, grounded answers from proprietary documents, optimizing for sub-200ms latency and high-concurrency scale. Strong MLOps/observability background: drift monitoring with Prometheus + Streamlit, automated retraining via Airflow, Kubernetes autoscaling, and MLflow-managed model lifecycle, plus inference cost reduction through quantization and structured pruning.”
MARCUS JOHNSON
Senior AI/ML Engineer specializing in Generative AI, NLP, and RAG systems
“ML/NLP engineer focused on production-grade data and search/recommendation systems: built an end-to-end pipeline that connects unstructured customer feedback with product data using TF-IDF/BERT, Spark, and AWS (SageMaker/S3), orchestrated with Airflow and monitored for drift. Also has hands-on experience with entity resolution at scale and improving search relevance via BERT embeddings, FAISS vector search, and domain fine-tuning validated with precision@k and A/B testing.”
Jim Glassman
Executive Technology Leader specializing in Enterprise AI, Cloud Architecture, and Data Platforms
“Senior data/technology executive who stays hands-on: currently building a Go micro-kernel orchestration layer for medical AI agents to boost concurrency and enforce HIPAA/PHI controls, achieving 26x throughput on migrated workloads. Has led large-scale transformations across healthcare and financial services, including a 45-day data warehouse rebuild at Elara Caring and a data/ML roadmap at Acelity credited with $230M in annual revenue impact prior to 3M acquisition.”
Mid-level AI/ML Engineer specializing in NLP, computer vision, and MLOps
Intern AI/ML Engineer specializing in LLM agents, RAG, and computer vision
Mid-level Machine Learning Engineer specializing in NLP, recommender systems, and on-device ML
Software Engineering Intern specializing in backend APIs, Kafka data pipelines, and cloud systems
Staff Software Engineer specializing in FinTech, AI/ML, and cloud microservices