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Vetted Hyperparameter Tuning Professionals
Pre-screened and vetted.
Mid-level Machine Learning Engineer specializing in MLOps and cloud-native ML systems
Senior Data Scientist specializing in NLP, LLMs, and Generative AI automation
Mid-level AI/ML Engineer specializing in Generative AI agents and FinTech risk systems
Mid-level Machine Learning Engineer specializing in LLM personalization and scalable MLOps
Staff Machine Learning Engineer specializing in LLMs and cloud-native AI platforms
Mid-level Machine Learning Engineer specializing in real-time recommender systems and MLOps
Mid-level AI/ML Engineer specializing in LLMs, RAG, and multi-agent systems
Junior Data Analyst specializing in experimentation, data quality, and ML analytics
Mid-level AI/ML Engineer specializing in RAG, NLP, and MLOps
Pavithra Kollu
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and search systems
“Backend/ML infrastructure engineer with experience at Perplexity and Meta building production evaluation, monitoring, and retrieval systems for AI search, autonomous agents, and LLM-powered workflows. Particularly strong in turning messy manual quality-review processes into reusable Python/FastAPI automation with measurable impact, including major gains in search relevance, latency, and grounded answer quality.”
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-level 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.”
Jiayi Zhang
Junior Full-Stack Engineer specializing in AI automation for FinTech and logistics
“Full-stack product engineer focused on operational automation with AI in invoice, billing, and shipment workflows. Has shipped production systems using OpenAI APIs and AI agents that materially reduced manual work and cut bill transcription costs by 99%, while also improving UX through human-in-the-loop interfaces and performance tuning.”
Mid-level Data Scientist specializing in ML for healthcare and strategy analytics
Mid-level AI/ML Engineer specializing in FinTech risk and fraud systems
Mid-level Machine Learning Engineer specializing in generative AI, NLP, and MLOps
Senior AI Engineer specializing in machine learning, NLP, and generative AI
Sai supriya
Mid-level AI/ML Engineer specializing in LLM alignment, safety, and scalable inference
“Built and productionized an AWS-hosted, Kubernetes-orchestrated RAG assistant that enables natural-language Q&A over internal document repositories with grounded answers and citations. Demonstrates strong applied LLM engineering: hallucination mitigation, hybrid retrieval + re-ranking, and rigorous evaluation via benchmarks and A/B testing, plus real-world scaling of compute-heavy inference with dynamic batching and monitoring.”