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Vetted MLOps Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in recommender systems, NLP, and MLOps
Mid-level Full-Stack Developer specializing in FinTech and fraud detection
Mid-level AI/ML Engineer and Developer Educator specializing in GenAI, RAG, and AI community building
Mid-level AI/ML Engineer specializing in MLOps, distributed ML, and RAG pipelines
Senior Data Scientist specializing in Generative AI, NLP, and MLOps
Mid-level Data Engineer specializing in AI/ML data platforms and real-time streaming
Mid-level Data Engineer specializing in cloud lakehouse and streaming pipelines
Senior DevOps Engineer / AWS Solutions Architect specializing in Kubernetes and DevSecOps
Mid-level AI Backend Engineer specializing in LLM applications and scalable ML systems
Executive product and engineering leader specializing in FinTech and healthcare technology
Mid-level Software Engineer specializing in AI systems and FinTech
Senior AI/ML Engineer specializing in GenAI, LLMs, NLP, and MLOps
Senior AI/ML Engineer specializing in Generative AI and cloud-native ML systems
Rubeena Riyas
Senior AI Engineer specializing in LLM agents, RAG, and scalable data platforms
“ML/data engineer who owned an end-to-end production sales analytics pipeline at 15,000+ user scale, delivering ~50% compute reduction, ~80% faster reporting, and ~$1.2M impact. Also shipped a production RAG-based AI assistant over internal BigQuery/docs with evaluation metrics and safety guardrails, and built shared Python libraries to standardize reliability and accelerate engineering teams.”
Abhishikth Meesala
Mid-level AI/ML Engineer specializing in NLP, Generative AI, and fraud detection
“At PwC, built and productionized an agentic RAG enterprise search assistant over 6M internal documents (8M embeddings), deployed across AWS and GCP. Drove major retrieval gains (72%→92% precision via BM25+dense hybrid with RRF and cross-encoder re-ranking), reduced hallucinations 30%, achieved <2s latency at 50–60K queries/month, and cut support tickets 30%—boosting adoption to 2,500 users by adding source-cited answers.”
Varaprasad Bathula
Intern AI/ML Engineer specializing in LLM applications and data infrastructure
“Hands-on LLM practitioner who built a production document-processing pipeline in Python, tackling long-document handling and latency with chunking/batching and a user-driven correction feedback loop. Experienced operationalizing AI workflows with Kubernetes (CronJobs, autoscaling, scheduled data cleaning and weekly retraining) and applying structured testing/evaluation (E2E, LLM-as-judge, HITL) while communicating solutions clearly to non-technical clients using visual diagrams.”
Keith Aumiller
Director-level Data & AI Leader specializing in enterprise transformation
“Built Cigna Health’s risk-based management/monitoring system used as a primary product for pharmaceutical clients, supporting clinical trials and utilized during the COVID-19 pandemic. Currently running a community-based startup (details kept proprietary) and is open to executive roles or joining a strong team with a clear path to success, evaluating opportunities via ROI.”