Vetted Data Modeling Professionals

“Accenture data/ML practitioner who deployed a retail churn prediction and BERT-based sentiment analysis system to production, integrating behavioral + feedback data and operationalizing it with ETL automation, orchestration, and CI/CD. Experienced managing 2TB+ multi-source data, monitoring drift in Databricks, and translating results into Power BI dashboards for marketing teams (including K-means customer segmentation).”

“Built a production internal LLM-powered knowledge assistant using a RAG architecture (Python, LLM APIs, cloud services) that answers employee questions with sourced, grounded responses from internal documents. Demonstrates strong practical depth in retrieval tuning (chunking/metadata filters), orchestration with LangChain, and production reliability practices (latency optimization, automated embedding refresh, evaluation metrics, logging/monitoring) while partnering closely with non-technical operations teams.”

“Software engineer with hands-on ownership of both fintech checkout improvements (saved payment methods/one-click checkout with tokenization and feature-flag rollouts) and production LLM/RAG systems for customer support. Demonstrates strong operational rigor via guardrails, evaluation loops integrated into CI/CD, and scalable data pipelines handling messy PDFs/CSVs/logs with reliability and observability.”

“Distributed-systems engineer applying robotics-style patterns to software: built "Vibecheck," a high-throughput real-time video + OS-telemetry fusion and analysis system (500+ MB/session) with strict latency constraints. Strong in containerization and CI/CD (Docker, GitHub Actions) and in designing fault-tolerant, event-driven architectures (Kafka/RabbitMQ), plus hands-on debugging of multi-agent coordination using blackboard + watchdog/circuit-breaker control patterns.”

“Data engineer with healthcare and enterprise experience (Molina Healthcare, Dell Technologies) building and operating high-volume batch + streaming pipelines across AWS and Azure. Strong focus on data quality (schema validation, fail-fast checks), reliability (monitoring/alerts, retries), and performance tuning (Spark/partitioning), with measurable runtime reduction and improved downstream trust.”

“Data engineer (Charles Schwab) who took ownership of an unstable, ambiguous nightly financial data pipeline and rebuilt it into a reliable, incremental AWS Glue/Airflow/Redshift system feeding Power BI. Created a custom Python data-quality framework with hard-stop gating and schema drift detection, improving integrity (99.9%), cutting runtime (~20%), and reducing incidents/tickets (35% fewer schema-related dashboard incidents; 30% fewer investigations).”

Jaideep bommidi

Screened

Senior ML Engineer & Data Scientist specializing in LLM agents, retrieval/ranking, and MLOps

Denton, TX8y exp

“Machine Learning Engineer currently at Webster Bank building an enterprise-scale LLM agent for Temenos Journey Manager/Maestro, using RAG-style multi-stage retrieval with FAISS/Pinecone, hybrid dense+sparse search, and LoRA fine-tuning optimized via NDCG/MAP and A/B testing. Previously handled messy incident/telemetry data at Deuta Werke GmbH with deterministic + fuzzy entity resolution, and has strong production data engineering experience across Spark/Hadoop and Python ETL systems.”

Yaswanth Thota Thota

Screened

Mid-level Data Analyst specializing in financial risk and healthcare analytics

AZ, USA4y exp

“AI/ML engineer focused on real-time, production-grade LLM systems, with a robotics-adjacent mindset around latency/accuracy tradeoffs and modular pipelines. Built a scalable RAG-based assistant orchestrated as microservices on Kubernetes with Kafka async messaging, ONNX/quantization optimizations, and monitoring (Prometheus/Grafana), citing a ~35% hallucination reduction; has also experimented with ROS Noetic/Gazebo to understand ROS concepts.”

Bryan West

Screened

Senior Software Engineer specializing in AI, cloud infrastructure, and full-stack development

Chantilly, VA17y exp

“ML/NLP engineer who built a production system that converts large-scale unstructured text into a connected, searchable knowledge base using spaCy + Sentence Transformers/FAISS and a Neo4j knowledge graph, with BERTopic and XGBoost for organization/labeling. Strong focus on production-grade Python workflows (FastAPI/Celery, Pydantic validation, Docker, AWS ECS/Lambda) and robust entity resolution with measurable precision/recall and human review for low-confidence matches.”

Sai Harshith Tanguturi

Screened

Mid-Level Software Engineer specializing in Java microservices and AWS cloud-native systems

Grapevine, TX3y exp

“Full-stack engineer who has owned customer-critical analytics and course intelligence platforms end-to-end (React/TypeScript + Node/Express + SQL), including an internal self-serve Reporting & Analytics Center adopted by 1,000+ users. Demonstrates strong systems thinking across performance (2× faster heavy reports), reliability (feature flags, testing), and distributed architecture (RabbitMQ microservices with idempotency, DLQs, and correlation-ID observability).”

Mohan Naik Megavath

Screened

Mid-level Data Engineer specializing in real-time pipelines and cloud data platforms

Remote, USA4y exp

“Backend engineer with hands-on experience building secure Python/Flask services (sessions, JWT, RBAC) and optimizing PostgreSQL/SQLAlchemy performance, including custom SQL using CTEs/window functions profiled via EXPLAIN ANALYZE. Also integrates LLM features via OpenAI/Azure into backend systems and improves scalability with RabbitMQ-driven async processing, caching, and multi-tenant data isolation patterns.”

Ti Wu

Screened

Junior Full-Stack Developer specializing in web apps and reinforcement learning

Hsinchu, Taiwan1y exp

“Built an AI basketball shooting coach that analyzes player form against NBA players and recruited 30+ beta users via Reddit to drive iterative UI/workflow improvements. Also has internship experience building an administrative server and coordinating API/database compatibility with another client server, emphasizing communication and integration quality.”

Aditya Agrawal

Screened

Intern Software Engineer specializing in backend systems and data engineering

1y exp

“Backend/AI engineer who has built and shipped two products: Know Founder (Python/SQL/AWS) scaling to 2,000+ users in the first month, and Unifr (unifr.online), an AI search visibility engine that queries multiple LLMs and turns responses into structured brand insights. Strong in production reliability/performance (Redis caching, indexing, precomputation) and in designing agentic workflows with guardrails, validation, retries, and human escalation.”

UMESH KAMISETTY

Screened

Mid-level Data Engineer specializing in cloud lakehouse and streaming platforms

Seattle, WA5y exp

“Data engineer focused on building production-grade pipelines on AWS (Kafka/Kinesis/Glue/S3) through to curated serving layers in Snowflake and Delta Lake. Emphasizes automated data quality validation (PySpark + CI/CD), modular dbt transformations for analytics (customer spending, risk metrics), and operational reliability with CloudWatch and DLQs; data consumed by BI tools and ML pipelines for fraud detection and risk analytics.”

“Healthcare analytics candidate with hands-on experience turning messy claims data in Redshift and S3 into validated reporting tables, plus automating KPI workflows in Python. They’ve owned end-to-end operational analytics projects, including a claims delay analysis that improved processing efficiency by about 20%, and have experience driving stakeholder adoption of standardized metrics across dashboards.”

Ravindrareddy B

Screened

Junior Full-Stack Java Developer specializing in enterprise web applications

Ames, IA2y exp

“Full-stack engineer with hands-on experience building an internal telecom order-tracking/dashboard platform at T-Mobile across React, Spring Boot, and PostgreSQL. Stands out for owning features end-to-end, from scalable frontend architecture and TypeScript patterns to API design, query optimization, CI/CD, and post-launch monitoring in AWS CloudWatch.”

“Healthcare product leader with substantial experience in clinical software, medical devices, analytics, and AI/ML-enabled workflows. They have led a cloud analytics platform for hospital systems, managed a machine-learning insulin dosing product in a safety-critical environment, and driven UX modernization of clinician-facing applications while coordinating deeply across engineering, QA, data science, DevOps, and customer success.”

“B2B SaaS presales/solutions engineer with recent experience spanning Cisco enterprise infrastructure and AI-driven POS analytics products. Supported 120+ enterprise accounts, helped drive a $10M renewal/expansion in financial services, and combines classic enterprise SE skills with hands-on API, SSO/SAML, ETL, Python, SQL, and LLM/RAG integration experience.”

“Early-career solutions engineer with experience spanning Dell Technologies and insurance operations, combining enterprise hybrid cloud pre-sales exposure with hands-on AI and API integration work. Completed a master's at Illinois Institute of Technology while building customer-facing experience in technical discovery, POCs, security/compliance discussions, and workflow automation.”

“Full-stack engineer who owned an enterprise AI agent automation platform at KeyBank, building React/TypeScript interfaces and Python/AWS microservices for document-heavy business workflows. Stands out for translating complex AI automation into usable products for non-technical users, with reported productivity gains of about 35% and reduced manual processing.”

“AI/full-stack product engineer with experience shipping agentic systems in both fintech and enterprise compliance contexts, including an Anthropic-powered compliance Q&A tool at American Express and a home-equity assessment experience for seniors. Stands out for combining strong product instincts, typed full-stack implementation, and rigorous LLM evaluation/monitoring practices to improve trust, adoption, and operational efficiency.”

Emily MacPherson

Screened

Senior finance and business operations leader specializing in technology financial management

San Francisco, CA14y exp

“Finance leader with roots in telecom and utilities who evolved from FP&A and product analysis into strategic technology business management. They have built cost transparency and total-cost-of-ownership capabilities for large-scale agile product transformations, delivering $41M in expense impact and helping reprioritize $200M+ in capital investments.”

“Engineer with experience in small, high-pressure innovation environments and enterprise healthcare platforms, spanning distributed systems, search, and database optimization. At RJ Lee Group, he helped pivot an Air Force document-processing platform from Pig/MapReduce to Apache Storm, enabling near-real-time results, and also built a full-stack natural-language search application that cut analyst investigations from months to weeks or days.”