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Vetted scikit-learn Professionals
Pre-screened and vetted.
Senior Machine Learning Engineer specializing in conversational AI and InsurTech
Senior AI/ML Engineer specializing in healthcare and fintech AI systems
Senior Full-Stack Python Developer specializing in cloud, data platforms, and GenAI
Mid-level Machine Learning Engineer specializing in fraud detection and recommendations
Mid-level Agentic AI & ML Engineer specializing in LLM agents and RAG systems
Mid-level Data Scientist specializing in GenAI, LLMs, and MLOps
Senior Software Engineer specializing in cloud microservices and data pipelines
Senior Full-Stack Software Engineer specializing in cloud platforms and AI integration
Junior Data Scientist & Data Engineer specializing in ML and scalable data pipelines
Executive Engineering Leader specializing in E-commerce, SaaS, and EdTech platforms
Senior Software Engineer specializing in cloud, data platforms, and LLM/RAG applications
Mid-level AI/ML Engineer specializing in cloud MLOps and GenAI for fraud detection
Mid-level Data Scientist specializing in FinTech and product analytics
Mid-level Full-Stack Software Engineer specializing in cloud-native and data platforms
Senior AI & Systems Architect specializing in ML infrastructure and FinTech
Surya Teja
Mid-level Backend/Full-Stack Engineer specializing in AI and FinTech payments
“Full-stack engineer who has owned an operational reporting/dashboard product end-to-end—building a React UI, designing/implementing FastAPI services, and deploying/operating on AWS. Demonstrates strong performance engineering (Postgres query/index tuning using EXPLAIN ANALYZE) with concrete impact (reports reduced from tens of seconds to a few seconds) and a reliability mindset across observability, migrations, and resilient third-party/ETL integrations.”
Deekshit Myakala
Mid-level Software Engineer specializing in cloud automation and data/ETL platforms
“Backend engineer with AWS multi-region production experience building APIs and workflow automation for data center/storage hardware operations (firmware orchestration, maintenance checks, ticketing, dashboards). Also shipped an internal AI chat tool that parses hardware runbooks and incorporates user feedback to retrain the model, and has a strong testing/quality discipline (95%+ coverage) plus database performance tuning via indexing and query monitoring.”
Jagadeesh Kakamolu
Mid-level Software Engineer specializing in backend, cloud, and AI systems
“Engineer with hands-on experience across backend, full-stack, cloud, and AI/ML systems, with particular depth in Python, FastAPI, AWS Bedrock, SageMaker, and RAG-based architectures. Stands out for treating AI and agents as accelerators within disciplined production engineering, emphasizing guardrails, observability, latency/cost monitoring, and scalable system design.”