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Vetted scikit-learn Professionals
Pre-screened and vetted.
Abdelmonaim Serrhini
Senior Full-Stack Engineer specializing in Spring Boot, React, and Next.js
“Full-stack engineer and Scrum Master who led a major monolith-to-microservices migration, including a micro-frontend Angular architecture using Native Federation and staged integration into the legacy app. Also built a React + TypeScript “Business Risk” product featuring a metadata-driven dynamic dashboard/forms layer backed by Spring Boot + GraphQL, with strong QA practices (unit/integration/E2E via Cypress), CI/CD, and feature toggles.”
Sujal Bais
Junior AI/ML Engineer specializing in applied machine learning and data pipelines
“Built and deployed an LLM-powered automation pipeline that ingests voice and documents, transcribes/extracts key information into structured data, and routes it through backend workflows using Python/FastAPI. Uses n8n to orchestrate multi-step AI processes with validation, retries, and monitoring, and iterates with stakeholders via rapid demos to refine changing requirements.”
MUHAMMAD KHUSHAL KHAN
Mid-level Quantitative Developer specializing in low-latency trading systems
“Backend/ML engineer with deep fintech and marketplace experience: built a real-time financial analytics + algorithmic trading platform (Python/Postgres/Kafka/Redis) and drove major DB performance wins (10x faster analytics; sub-10ms response consistency). Also shipped an end-to-end ML recruitment matching platform (scraping/ETL/modeling/Django deployment) with reported 92% matching accuracy, and emphasizes production reliability via monitoring, blue-green deploys, and robust workflow error handling.”
Aditya Reddy Gunda
Intern AI/ML & Data Engineer specializing in deep learning, NLP, and cloud data pipelines
“AI/ML practitioner with production experience building a RAG-powered contextual customer support agent, optimizing for low latency using vector databases and smaller LLMs. Also deployed a fraud detection model on Kubernetes with auto-scaling for heavy transactional loads, and improved chatbot accuracy by 15% through metric-driven testing and evaluation. Partners with Marketing on personalization/recommendation initiatives with measurable outcomes tied to customer feedback.”
Entry-Level Full-Stack AI Engineer specializing in RAG pipelines and enterprise SaaS
Junior Software Engineer specializing in full-stack development and machine learning
Junior Full-Stack Software Engineer specializing in AI and e-commerce automation
Junior Full-Stack/ML Engineer specializing in web automation and NLP
Mid-level Full-Stack Product Engineer specializing in backend systems and AI developer tools
Junior Full-Stack & Machine Learning Engineer specializing in observability tools
Junior Full-Stack Software Developer specializing in cloud-native apps and data/AI
Senior Full-Stack & AI Engineer specializing in scalable web and cloud applications
Mid-level Full-Stack Software Engineer specializing in cloud microservices and data/ML
Intern AI/ML Software Engineer specializing in NLP and model serving
Mid-level R&D Engineer specializing in applied AI, experimentation, and cloud-integrated prototypes
Mid-level Python Developer specializing in cloud-native APIs and microservices
Mid-level Research Assistant specializing in interpretable ML and AI evaluation
Junior Full-Stack Software Engineer specializing in web apps, cloud, and ML inference
Junior Full-Stack Software Engineer specializing in Spring Boot, React, and mobile apps
Mid-level AI/ML Engineer specializing in LLMs and RAG systems
Mid-level Python Backend Engineer specializing in microservices and AWS