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Vetted Algorithms Professionals
Pre-screened and vetted.
Mid-level Full-Stack Developer specializing in Spring Boot microservices and React
Junior Software Engineer specializing in full-stack development and data pipelines
Mid-Level Full-Stack Software Engineer specializing in AI/ML and cloud-native microservices
Junior Technical Artist specializing in real-time 3D, shaders, and VR/AR
Entry-Level Software Engineer specializing in Linux and backend systems
Mid-level Full-Stack Engineer specializing in cloud-native microservices
Junior Full-Stack Software Engineer specializing in cloud-native microservices
Senior Full-Stack Developer specializing in cloud-native FinTech systems
Senior AI/Software Engineer specializing in multi-agent LLM orchestration and data engineering
Senior Full-Stack Software Engineer specializing in Python backends and React frontends
Senior Full-Stack Java Developer specializing in cloud-native microservices (FinTech/Healthcare)
Mid-level Computer Science PhD Researcher specializing in privacy-preserving sensing and HCI
Junior Software/ML Engineer specializing in cloud platforms and applied machine learning
Junior Software Engineer specializing in autonomous vehicle perception and MLOps
Manyuvraj Sandhu
Mid-level Full-Stack Developer specializing in Next.js, AI-driven apps, and payments
“Frontend engineer who has led complex React + TypeScript products end-to-end, including a real-time canvas-based digital signature editor and a multi-step AI workflow dashboard. Demonstrates strong architecture and performance instincts (state machines for streaming async updates, bundle/render optimizations) plus pragmatic shipping practices (feature flags, automated tests, analytics and user interviews), with a quantified impact from refactoring (~30% less duplicated UI code).”
Joseph Lin
Intern Software Engineer specializing in full-stack development and applied AI
“Internship experience building an end-to-end medical AI pipeline that extracts and normalizes messy medical PDFs, fine-tunes BioBERT to classify tumor-related statements (including negation/ambiguity handling), and integrates image-model outputs (MedSAM/GroundingDINO) for tumor localization and classification. Also worked on an LLM/RAG system to draft IPO prospectuses using retrieved regulatory/financial sources (including SEC EDGAR) with structured prompts to reduce hallucinations.”
Naga Gayatri Bandaru
Mid-level AI/ML Engineer specializing in MLOps and production ML systems
“Backend/ML engineer who has shipped high-scale real-time systems across e-commerce and healthcare: built a PharmEasy real-time recommendation engine for ~2M monthly users (cut feature latency 5 min→30 sec; +15% cross-sell) and architected a HIPAA-compliant multimodal clinical diagnostic workflow (DICOM+EHR) with XAI, MLOps (MLflow/Airflow/K8s), and drift/monitoring guardrails supporting 10k+ daily predictions.”