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Vetted ETL Pipelines Professionals
Pre-screened and vetted.
Ahmed Sadaqat
Senior Machine Learning Engineer specializing in production ML and predictive analytics
“ML/AI engineering leader who has owned end-to-end production systems from experimentation through deployment, monitoring, and iteration at meaningful scale. They describe running a 1M+ records/day prediction platform with 99.9% availability, shipping a RAG-based conversational AI feature for 50,000 active users, and consistently improving precision, latency, reliability, and cost with measurable business impact.”
Subhash Mothukuru
Mid-level Machine Learning Engineer specializing in LLMs, generative AI, and MLOps
“Built and shipped a production LLM-powered medical scribe that generates structured clinical visit summaries using RAG, strict JSON schemas, and post-generation validation to reduce hallucinations. Experienced in making LLM workflows deterministic and observable (structured logging/metrics/tracing) and in evaluation-driven iteration with metrics like schema pass rate and edit rate; collaborated closely with clinicians and policy stakeholders at Scale AI to drive adoption.”
Mohammed Reyaan
Mid-level Full-Stack Developer specializing in cloud-native web applications
“Frontend-leaning full-stack engineer who built an internal real-time operations dashboard from 0→1 using React, TypeScript, Redux Toolkit, Material UI, and Node.js integrations. Stands out for hands-on performance tuning at scale—profiling and fixing excessive re-renders, optimizing live-update UIs, and iterating post-launch with caching, pagination, and observability.”
Shashank Sathola
Mid-level Python Backend Developer specializing in cloud-native microservices and AI/ML platforms
“Backend/AI engineer who built a production GPU-backed real-time inference API at Nvidia and debugged burst-induced tail latency, cutting P95 by ~29% through dynamic batching and backpressure. Also shipped an end-to-end RAG + agentic operational diagnostics assistant with strict tool controls, evidence citation, confidence gating, and strong production guardrails, plus demonstrated hands-on Postgres optimization (900ms to 40–60ms).”
Mid-level Full-Stack Python Developer specializing in FinTech and ML-driven automation
Senior Software Engineer specializing in ML integrity and large-scale data pipelines
Entry-level Data & Quant Analytics professional specializing in finance and machine learning
Mid-level AI/ML Engineer specializing in GPU-accelerated LLMs, RAG, and production MLOps
Mid-level Security Engineer specializing in application security, IAM, and AI red teaming
Mid-level AI/ML Engineer specializing in LLMs, search ranking, and multimodal ML
Senior Machine Learning Engineer specializing in multimodal AI and biomedical data
Senior Full-Stack & AI/ML Engineer specializing in LLM and cloud-native platforms
Senior AI/ML Software Engineer specializing in LLMs, NLP, and scalable ML platforms
Mid-level Software Engineer specializing in backend distributed systems
Junior Robotics Perception Engineer specializing in computer vision and autonomous navigation
Senior AI/ML Engineer specializing in LLMs, RAG, and multimodal recommendation systems
Mid-level Machine Learning Engineer specializing in LLM personalization and scalable MLOps
Junior Software Engineer specializing in full-stack web and data platforms
Senior Full-Stack Engineer specializing in scalable cloud platforms and AI integrations
Mid-level AI/ML Engineer specializing in LLM fine-tuning, RAG, and MLOps
Senior Full-Stack Engineer specializing in AI/GenAI and cloud-native platforms