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Vetted Supervised Learning Professionals
Pre-screened and vetted.
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Mid-level Machine Learning Engineer specializing in Generative AI and LLM applications
Sabrish Kumar Pradeep Kumar
Mid-Level Software Engineer specializing in data pipelines, observability, and analytics
“Meta engineer who improved a critical revenue estimation dataset pipeline that was arriving ~6 days late—diagnosed via raw logs/lineage, redesigned legacy scans to only process the needed window, and shipped validation plus freshness/lag dashboards. Delivered ~50% latency reduction (to ~3 days) and regained adoption by running old/new pipelines in parallel with gated cutover and evidence-based customer communication. Applies incident-response rigor to real-time LLM/agentic workflow debugging and regularly runs developer demos/workshops.”
Ravikanth Kasamsetty
Executive AI/ML Engineering Leader specializing in cloud-native SaaS and GenAI platforms
“Engineering leader who modernized and unified a fragmented product suite at Milestone via a multi-year cloud-native roadmap, delivering an MVP in three quarters and boosting team velocity by 40% through cross-functional squads. At Prometheum, led a trust-building hybrid architecture (AWS control plane + customer-hosted data plane) using Kubernetes to ensure sensitive enterprise data never left customer networks while remaining cloud-agnostic across providers.”
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.”
Mid-level Machine Learning Engineer specializing in MLOps and cloud-native ML systems
Mid-level AI/ML Engineer specializing in LLMs, RAG pipelines, and multi-agent systems
Senior AI/ML Software Engineer specializing in LLMs, NLP, and scalable ML platforms
Intern Software Engineer specializing in data engineering and LLM evaluation
Mid-level Machine Learning Engineer specializing in LLMs, ranking, and scalable ML systems
Mid-level Machine Learning Engineer specializing in LLM personalization and scalable MLOps
Mid-level AI/ML Engineer specializing in LLM fine-tuning, RAG, and MLOps
Mid-level Machine Learning Engineer specializing in real-time recommender systems and MLOps
Senior Data Scientist specializing in large-scale ML systems and recommendations
Mid-level AI/ML Engineer specializing in RAG, NLP, and MLOps
Mid AI/ML Engineer specializing in LLMs, RAG, and multimodal systems
Harish Kasu
Mid-level AI/ML Engineer specializing in Generative AI, RAG, and MLOps
“AI/LLM engineer with production experience at NVIDIA and Microsoft, including building a RAG-based enterprise knowledge assistant that improved accuracy by 42% and scaled to thousands of queries. Deep in inference optimization (TensorRT-LLM, Triton, quantization, speculative decoding) and MLOps/observability (Prometheus/Grafana, MLflow, LangSmith), plus orchestration with Kubeflow/Airflow across multi-cloud.”
Vinay Ramrupe
Mid AI/ML Engineer specializing in LLM and enterprise generative AI
“ML/AI engineer focused on taking LLM systems from experimentation to reliable production, including enterprise copilot and RAG-based knowledge retrieval use cases. Stands out for combining data pipelines, model training, inference optimization, automated evaluation, and safety guardrails, with cited impact including 20% throughput gains and 30% less manual evaluation effort.”
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and scalable GPU inference