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Vetted Databricks Professionals
Pre-screened and vetted.
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
Mid-level Data Engineer specializing in cloud data pipelines and lakehouse/warehouse platforms
Staff Software Engineer specializing in FinTech, AI/ML, and cloud microservices
Mid-level Data Engineer specializing in cloud data platforms and streaming pipelines
Executive AI transformation leader specializing in healthcare and enterprise modernization
Principal Data Engineer specializing in cloud-native AI and data platforms
Intern Software Engineer specializing in AI/ML and LLM retrieval systems
Senior Technology Consultant specializing in cloud, data engineering, and AI solutions
Mid-level Generative AI & Machine Learning Engineer specializing in LLMs and RAG
Mid-level Data Engineer specializing in cloud-native big data pipelines and analytics
Senior Data Engineer specializing in cloud data platforms and real-time analytics
Senior Data Engineer specializing in cloud data platforms and large-scale ETL
Mid-level Data Engineer specializing in big data platforms and analytics infrastructure
Principal Data Scientist / AI Engineer specializing in healthcare-native AI platforms
Alexander Choy
Director of AI/ML Engineering specializing in MLOps, data platforms, and 3D computer vision
“Backend/data engineer focused on production ML/LLM systems: built a real-time FastAPI inference API on Kubernetes with strong reliability patterns (timeouts, idempotent retries, centralized error handling). Delivered AWS platforms using EKS + Lambda with GitHub Actions/Helm CI/CD and built Glue-based ETL from S3/Kafka into Snowflake with schema evolution and data-quality controls; also modernized legacy analytics/recommendation workflows into Python services with safe, feature-flagged cutovers.”
Gowri Kajipuram
Mid-level AI/ML Engineer specializing in LLMs, RAG, and multimodal deep learning
“ML/LLM engineer who has built and productionized a large multimodal LLM pipeline end-to-end—fine-tuning a 20B+ parameter model with distributed/FSDP training and deploying on Kubernetes via Triton for ~5x throughput. Strong focus on reliability and safety (monitoring with SHAP, guardrails, A/B testing) with reported ~22% relevance lift and reduced harmful/incorrect outputs, plus experience orchestrating ETL/retraining workflows with Airflow across S3/Snowflake/RDS.”
Jeremiah Medina
Senior AI/ML Engineer specializing in LLMs, RAG, and cloud-native MLOps
“Built and owned a real-time clinical AI assistant at Andor Health, taking it from prototype through deployment, monitoring, and iterative improvement. Brings strong healthcare-focused GenAI experience across RAG, hybrid retrieval, LoRA fine-tuning, and production Python services, with measurable gains in accuracy, speed, and reliability.”
Veer Arora
Junior Data Scientist specializing in ML, NLP, and healthcare analytics
“Built and deployed a healthcare NLP application that used an LLM-style physician interface feeding a random forest model to predict treatment plans for hard-to-triage patient subgroups, backed by a Databricks medallion pipeline and heavy feature engineering to address missing/low-integrity data across ~50K patients. Also delivered an earlier Microsoft AI Builder automation that improved transportation bill payment workflows by training non-technical payroll/procurement teams to use automated outstanding-payables reporting.”
Dhruv Arora
Senior Generative AI Implementation Consultant specializing in RAG and agentic AI on cloud
“LLM/RAG practitioner who built an AWS-based enterprise document search and summarization platform with RBAC and scaled it to 10K+ users, solving relevance issues via contextual chunking and hybrid retrieval. Also designed agentic workflows for a telecom forecast-validation use case using sub-agents, tool APIs, and strict context management, and has proven pre-sales influence (supported a $300K manufacturing deal with a roadmap-driven pitch).”