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Vetted MLOps Professionals
Pre-screened and vetted.
Mid-level GenAI/MLOps Engineer specializing in banking and healthcare LLM applications
Mid-level Machine Learning Engineer specializing in MLOps, fraud detection, and data security
Mid-level Full-Stack Software Engineer specializing in cloud microservices and FinTech
Mid-level AI/ML Engineer specializing in Generative AI agents and workflow automation
Mid-level Machine Learning & AI Engineer specializing in LLMOps, digital twins, and RL
Mid-level Machine Learning Engineer specializing in MLOps and Generative AI
Senior Machine Learning Software Engineer specializing in Azure enterprise AI
Junior Software Engineer specializing in AI automation and full-stack delivery
Mid-level Data Science & AI/ML Engineer specializing in MLOps, NLP, and computer vision
Junior Machine Learning Software Engineer specializing in cloud-deployed predictive models
Mid-level Data Scientist specializing in ML, NLP, and LLM-powered analytics
Mid-level Machine Learning Engineer specializing in production ML, MLOps, and Generative AI
Mid-level AI Software Engineer specializing in LLMs, NLP, and MLOps for healthcare
Mid-level AI/ML Engineer specializing in FinTech and production ML systems
sai anuragh Sangoju
Mid-level AI/ML Engineer specializing in fraud detection, credit risk, and NLP
“Built and deployed a production LLM-powered university support chatbot on Azure using a RAG pipeline, focusing on reducing hallucinations, improving latency, and handling ambiguous queries via confidence checks and clarification prompts. Also has hands-on orchestration experience (Airflow/Azure Data Factory), including hardening a demand-forecasting ingestion workflow with sensors, retries, and automated alerts, and uses a metrics-driven testing/monitoring approach for reliable AI agents.”
Mark Wlodawski
Senior Unity Developer specializing in AI/LLM systems and multiplayer VR
“Backend/data engineer focused on AWS-native Python systems: built a FastAPI microservice on ECS/Fargate serving real-time analytics at millions of daily requests with strong reliability (OAuth2/JWT, retries/timeouts, correlation IDs) and autoscaling. Also delivered Glue/PySpark ETL pipelines to curated S3 Parquet/Athena with schema evolution + data quality controls, owned Airflow pipeline incidents, and has a track record of measurable performance and cost optimizations (e.g., ~80%+ query latency reduction; reduced logging/NAT/Fargate spend).”
Yashwanth Penugonda
Mid-level AI/ML Engineer specializing in LLMs, RAG, and production GenAI systems
“Built and deployed a production LLM-powered RAG knowledge system to unify operational/policy information across PDFs, wikis, and databases, emphasizing auditability and low-latency/cost performance. Improved answer relevance at scale by moving from pure vector search to hybrid retrieval with metadata filtering and reranking, and partnered closely with healthcare operations/compliance to define acceptance criteria and human-in-the-loop guardrails.”