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Vetted Model Evaluation Professionals
Pre-screened and vetted.
Yousef Abdelsalam
Junior Software Engineer specializing in Odoo, web performance, and backend systems
“Full-stack developer who shipped LLM-powered customer support automation, including an AI call center designed for always-on, high-concurrency real-time phone handling. Also built a WhatsApp lead-conversion chatbot using Zapier webhooks, Redis state, and Twilio messaging, and reports measurable outcomes (+11% customer satisfaction, ~7% cost reduction) while using GPT-4.1.”
Lakshmi sailaja
Mid-Level Software Engineer specializing in backend microservices and AI/ML integration
“Built and shipped production LLM-driven pipelines for clinical data processing, turning semi-structured inputs into validated structured outputs for downstream analytics. Emphasizes predictability and safety via strict JSON schemas, state-machine orchestration, backend-controlled tool calling, and robust fallbacks (rule-based checks/manual review) plus monitoring and offline/online evaluation loops; also has experience hardening workflows against messy ERP/finance data with idempotency and state tracking.”
Gowtham Alasakani
Junior Full-Stack Software Engineer specializing in AI and data pipelines
“Built and shipped a production AI assistant for a web-based loan/interest calculator that helped users understand EMI results and optimize inputs. Demonstrated full-stack ownership across responsive UI, Node.js APIs, and LLM integration, with a strong focus on prompt refinement, guardrails, caching, fallbacks, and post-launch iteration driven by logs and user behavior.”
Ekta Mulkalwar
Junior Machine Learning & Full-Stack Engineer specializing in applied AI systems
“Master’s thesis focused on building and deploying a gait-based biometric authentication system using mobile accelerometer time-series data as an alternative to passwords/2FA. Emphasized real-world robustness by addressing sensor noise and variability (phone placement, walking speed, footwear) and improving safety using biometric metrics like FAR/FRR and EER, while collaborating closely with a non-ML thesis advisor.”
Mid-Level Full-Stack Software Engineer specializing in data pipelines, mobile apps, and AWS
Mid-Level Full-Stack Software Engineer specializing in cloud-native security & compliance platforms
Mid-level Data Scientist / AI Research Engineer specializing in LLMs, RAG, and applied ML
Junior Software Engineer specializing in full-stack development and applied AI
Mid-level AI/ML Engineer specializing in LLM-powered RAG systems and MLOps
Mid-level Full-Stack/AI Engineer specializing in LLM microservices, RAG, and data pipelines
Junior Software Engineer specializing in AI and full-stack development
Mid-Level Full-Stack Software Engineer specializing in healthcare web apps and LLM integrations
Mid-level AI/ML Engineer specializing in LLM agents, RAG pipelines, and AI automation
Junior Machine Learning Engineer specializing in healthcare and IT analytics
Mid-level Data Scientist specializing in ML, NLP, and Generative AI
Intern Machine Learning & Computer Vision Engineer specializing in 3D reconstruction
Junior Machine Learning Engineer specializing in LLMs and multimodal AI
Entry-level Machine Learning Engineer specializing in LLMs, RAG, and data pipelines
Junior Generative AI Engineer specializing in LLM systems and RAG
Mid-level Generative AI Engineer specializing in LLMs, RAG, and prompt engineering
Junior Software Engineer specializing in data analytics and machine learning
Mid-level AI/ML Engineer specializing in Generative AI, NLP, and RAG systems
Mid-level Generative AI Engineer specializing in LLMs, RAG, and agentic systems