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Vetted Data Modeling Professionals
Pre-screened and vetted.
Mid-Level Software Engineer specializing in full-stack systems and cloud platforms
Mid-level AI/ML Data Engineer specializing in analytics, ML pipelines, and LLM applications
Mid-level Full-Stack Developer specializing in FinTech and fraud detection
Mid-level Full-Stack Developer specializing in React, Node.js, and cloud-native AWS systems
Mid-level Data Scientist specializing in marketing analytics and scalable data platforms
VP Data Engineer specializing in AI-driven analytics platforms for investment management
Junior Full-Stack Software Engineer specializing in SaaS and AI-powered web apps
Mid-level Data Engineer specializing in AI/ML data platforms and real-time streaming
Mid-level Data Engineer specializing in cloud lakehouse and streaming pipelines
Mid-level Data Engineer specializing in AWS, Spark, and streaming data pipelines
Mid-level Data Engineer specializing in cloud-native ETL and data warehousing
Mid-level AI Backend Engineer specializing in LLM applications and scalable ML systems
Staff Salesforce Engineer specializing in enterprise CRM and integrations
Senior Software Engineer specializing in data platforms and FinTech/SaaS systems
Director of Engineering specializing in AI/ML, data platforms, and consumer messaging
Senior Full-Stack Engineer specializing in Java microservices and FinTech
JYOTHI N
Senior Data Scientist specializing in analytics, experimentation, and BI on AWS
“Data/ML practitioner focused on healthcare data quality and record linkage: analyzed 10M+ records, built anomaly detection and NLP-driven entity resolution, and automated AWS ETL/validation pipelines (Glue/Redshift/Lambda), cutting data errors by 40% and generating $500k in annual savings. Has hands-on experience with embeddings (Sentence Transformers/spaCy), FAISS vector search, and fine-tuning for domain-specific matching.”
Varaprasad Bathula
Intern AI/ML Engineer specializing in LLM applications and data infrastructure
“Hands-on LLM practitioner who built a production document-processing pipeline in Python, tackling long-document handling and latency with chunking/batching and a user-driven correction feedback loop. Experienced operationalizing AI workflows with Kubernetes (CronJobs, autoscaling, scheduled data cleaning and weekly retraining) and applying structured testing/evaluation (E2E, LLM-as-judge, HITL) while communicating solutions clearly to non-technical clients using visual diagrams.”
Jugal Rayala
Mid-level Full-Stack Developer specializing in AI-powered cloud applications
“Full-stack engineer who has owned customer-facing AI recommendation and analytics dashboards end-to-end (backend APIs/data processing through React UI, deployment, and monitoring). Demonstrates strong systems thinking around scaling microservices—using observability, caching, async workflows, and resilience patterns—and also built an internal ops dashboard that became the default tool for on-call incident reviews.”
Praneeth Regonda
Mid-level Full-Stack Engineer specializing in FinTech and AI platforms
“Full-stack engineer with 3 years of AI/ML experience who has shipped production LLM workflows, including a Bloomberg triage dashboard that cut manual processing by 35%. Combines React/TypeScript product sense with AWS/Spring/Lambda backend architecture and unusually strong practical judgment around evals, trust, retrieval, latency, and UX for real-world AI systems.”