Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in Generative AI, NLP, and healthcare RAG systems
“Built and deployed a production clinical claim validation RAG system at GE HealthCare that automated nurses’ patient-history/claims checks, cutting manual review time by ~65%. Designed the full stack (retrieval, embeddings, Pinecone, prompt/verification guardrails, FastAPI backend) with PHI-compliant anonymization via NER and orchestrated pipelines using Airflow, Azure ML Pipelines, and MLflow with drift monitoring.”
Mid-level Machine Learning Engineer specializing in Healthcare AI and Generative AI
“Analytics professional with Intuit experience spanning modern data stack work, behavioral segmentation, and applied AI. They built dbt/Snowflake pipelines powering retention and churn dashboards, automated feedback classification with OpenAI/LangChain, and partnered closely with product and marketing teams to turn analytics into onboarding, targeting, and lifecycle messaging decisions.”
Mid-level Software Engineer specializing in AI/ML and full-stack systems
“Data Scientist (2–3 years) at ZS Associates who has built and productionized agentic LLM systems, including a LangGraph-based multi-LLM prompt-optimization pipeline for entity extraction deployed as a Spring Boot microservice via Jenkins. Also built an Insightmate.ai chatbot and improved its RAG accuracy by diagnosing vector retrieval issues and implementing HyDE query expansion, while partnering with sales and pharma stakeholders to drive adoption (e.g., Zimmer Biomet platform migration into a multi-year partnership).”
Junior Marketing Analytics professional specializing in B2B SaaS and AI-driven insights
“Analytics professional with hands-on experience building SQL and Python workflows for marketing, funnel, and revenue reporting across tools like Salesforce, Google Analytics, and Power BI. They stand out for turning messy, multi-source data into trusted reporting layers, aligning sales and marketing on shared KPI definitions, and using segmentation/cohort analysis to improve campaign targeting and conversion performance.”
Senior AI/ML Engineer specializing in supply chain and healthcare systems
“Built and deployed AcademiQ Ai, a production LLM-based teaching assistant using GPT/BERT with RAG (LangChain + Pinecone) to handle large student notes and generate adaptive explanations/quizzes. Demonstrated measurable retrieval-quality gains (18% precision improvement, 22% less irrelevant context) by tuning similarity thresholds and chunking based on user satisfaction signals. Also orchestrated terabyte-scale, real-time demand forecasting pipelines using Airflow and Kubeflow on GCP with strong monitoring, shadow deployment, and feedback-loop practices.”
Senior Machine Learning Engineer / Data Scientist specializing in LLMs, RAG, and MLOps
Junior Data Scientist specializing in ML, NLP, and Computer Vision
Mid-level Data/Platform Engineer specializing in healthcare insurance analytics and API-first AI systems
Staff Software Engineer specializing in AI infrastructure, developer platforms, and Web3
Mid-level Full-Stack Software Engineer specializing in cloud microservices and data-driven apps
Junior Full-Stack Software Engineer specializing in cloud platforms and RAG/LLM evaluation
Executive Technology Leader specializing in AI-native SaaS and enterprise platforms
Executive technology leader specializing in product engineering, AI systems, and platform scale
Principal Full-Stack Architect specializing in AI, cloud, and enterprise platforms
Principal AI/ML Engineer specializing in credit risk and healthcare predictive modeling
Junior Software Engineer specializing in backend Python and cloud-native microservices
Mid-Level Full-Stack Software Engineer specializing in cloud-native distributed systems and AI
Senior Backend/Cloud Developer specializing in Python and AWS-native data workflows
Senior ML/AI Software Engineer specializing in GenAI, RAG, and cloud-native MLOps
Mid-level AI/ML Engineer specializing in LLMs, Generative AI, and MLOps