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Vetted MLOps Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in LLM fine-tuning and RAG systems
Senior Customer Success & Technical Account Leader specializing in AI/ML infrastructure
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
Mid-level Full-Stack Python Engineer specializing in AI search and distributed systems
Executive AI product leader specializing in healthcare and enterprise transformation
Senior Full-Stack Engineer specializing in AI/ML, LLMs, and RAG systems
Senior Machine Learning Engineer specializing in LLMs and Generative AI
Senior Full-Stack Engineer specializing in telehealth and commerce platforms
Senior Software Engineer specializing in full-stack platforms, MLOps, and LLM search
Mid-level AI Solutions Architect & Product Leader specializing in enterprise GenAI systems
Senior Full-Stack Engineer specializing in AI, cloud, and enterprise platforms
Rhutwij Tulankar
Engineering Manager and ML/Data Architect specializing in scalable data platforms and personalization
“Hands-on engineering manager at a marketing company leading a highly senior, distributed team (10 direct reports) while personally coding ~60–70% and owning end-to-end architecture across three interconnected products. Built agentic CRM automation and a reinforcement-learning-driven distribution layer for channel spend/bidding, with a strong focus on scalable design and observability (Prometheus/APM/logging) enabling frequent releases and few production incidents.”
Ashish Ernest Jeldi
Senior Data Scientist specializing in LLMs, agentic AI, and MLOps
“Built and shipped a production agentic LLM tool that helps internal teams update technical product whitepapers using plain-language edit requests, with strong guardrails (citations, verification, refusal/clarify flows) to reduce hallucinations and maintain compliance. Experienced taking LLM workflows from rapid LangChain prototypes to more predictable, debuggable LangGraph agent graphs, and orchestrating end-to-end ingestion/embedding/indexing/eval/deploy pipelines with Kubeflow.”
Andrew Fares
Mid-level Data Engineer specializing in AI, GenAI, and cloud data platforms
“Built production AI systems inside AWS finance/procurement, including an LLM-based supplier quote classification and price-vetting workflow that drove $5M in savings over 3 months. Combines GenAI evaluation expertise, internal platform design, and reusable Python data-quality tooling with strong cross-functional execution across finance, accounting, and hardware engineering.”
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.”