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Vetted Selenium Professionals
Pre-screened and vetted.
Senior Full-Stack Software Engineer specializing in scalable SaaS platforms
Senior QA Test Engineer specializing in automation and AR/VR testing
Senior Full-Stack Developer specializing in AI-driven cloud-native systems
Senior Software Engineer specializing in healthcare integrations, microservices, and AI-assisted systems
Mid-Level Software Engineer specializing in Java microservices and reactive systems
Mid-level Full-Stack Java Developer specializing in cloud-native microservices
Mid-level Full-Stack Software Engineer specializing in cloud-native microservices
Engineering Manager specializing in cloud-native platforms across AdTech and FinTech
Senior Software Engineer specializing in cloud-native microservices and real-time data pipelines
Mid-level Full-Stack Software Engineer specializing in microservices and cloud-native systems
Mid-level Full-Stack Developer specializing in microservices and AWS DevOps
Mid-level DevOps Engineer specializing in cloud-native CI/CD and Kubernetes
Mid-level Full-Stack Software Engineer specializing in cloud-native and AI-driven applications
Senior Site Reliability Engineer specializing in multi-cloud, Kubernetes, and observability
Rishitha Madipelli
Mid-level Software Engineer specializing in cloud-native distributed systems and streaming data
“Backend/product engineer with Tesla experience building and operating a real-time OTA update monitoring and fleet analytics platform at massive scale (telemetry from 3M+ vehicles). Delivered end-to-end systems across Kafka-based ingestion, TimescaleDB/Postgres analytics modeling, FastAPI/GraphQL APIs, and React/TypeScript dashboards, and handled production scaling incidents on AWS EKS during major rollout spikes.”
Prachi Jain
Mid-level Machine Learning Engineer specializing in NLP, LLMs, and MLOps
“Built and productionized a RAG-based analytics Q&A assistant for a financial analytics team, enabling natural-language querying across 200+ datasets (SQL tables, PDFs, compliance docs, wikis) and cutting turnaround time by 60%. Deep experience delivering regulated, audit-ready LLM systems on Azure (Azure OpenAI + LangChain) with strict grounding/citations, hybrid retrieval, and AKS-based low-latency deployment, plus strong collaboration with compliance analysts and auditors via iterative Gradio demos.”
Nikita Vivek Kolhe
Junior Data & Machine Learning Engineer specializing in MLOps and NLP
“ML/LLM practitioner with production experience building a healthcare review sentiment pipeline (RateMDs) using Hugging Face Transformers plus a LangChain+FAISS RAG layer for interactive querying. Also led orchestration-driven optimization of Nike’s Fusion ETL pipeline, improving runtime efficiency by 20%, and has experience translating ML outputs into Tableau dashboards for non-technical healthcare stakeholders (e.g., readmission risk).”