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Vetted scikit-learn Professionals
Pre-screened and vetted.
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 Data Analyst specializing in marketing and product analytics
Mid-level Full-Stack AI Engineer specializing in RAG systems and intelligent automation
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
Senior AI/ML Engineer specializing in NLP, LLMs, speech, and computer vision
Intern Data Science and Web Development student specializing in machine learning
Senior AI/ML Engineer specializing in NLP, LLMs, speech, and computer vision
Mid-level Python Backend Engineer specializing in microservices and AWS
Junior Software Engineer specializing in AI/ML, data pipelines, and real-time dashboards
Mid-level AI Engineer specializing in LLMs, RAG, and enterprise compliance & fraud systems
Junior Full-Stack Software Engineer specializing in cloud-native microservices and data pipelines
Senior AI/ML Engineer specializing in NLP, LLMs, speech, and computer vision
Senior AI Engineer specializing in LLMs, agentic systems, and ML infrastructure
Mid-level Machine Learning Engineer specializing in Generative AI and healthcare NLP
Intern Full-Stack Software Engineer specializing in AI-powered applications
Maulik Maganbhai Ghatala
Entry Backend Software Engineer specializing in Python/FastAPI and cloud-native APIs
“Backend engineer who built and evolved a low-latency document search platform (C++/gRPC on Kubernetes with a vector database), emphasizing resilience under concurrent load through strict deadlines, retries, idempotency, and observability. Also experienced building secure, frontend-friendly FastAPI services (Pydantic + JWT) and executing safe incremental refactors using feature flags and parallel validation.”