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Vetted Anomaly Detection Professionals
Pre-screened and vetted.
Benjamin Ung
Senior Machine Learning Software Engineer specializing in computer vision and simulation
“Robotics engineer who worked on a lunar rover program, building a simulation environment that mirrored real hardware interfaces and incorporated moon-terrain slip/friction modeling validated against a physical “moon yard.” Also integrated an ML-based munition X-ray inspection system via REST APIs, deploying and scaling inference on Azure with Kubernetes plus Prometheus monitoring, load balancing, and self-healing reliability mechanisms.”
YAKKALI PAVAN
Mid-level Machine Learning & Generative AI Engineer specializing in NLP, CV, and RAG systems
“Built and deployed a production LLM-powered RAG document intelligence system used by non-technical enterprise stakeholders, cutting document search time by 40%+ while improving answer consistency. Demonstrates strong MLOps/data workflow orchestration (Airflow, AWS Step Functions, managed schedulers across GCP/Azure) and a metrics-driven approach to reliability, evaluation, and cost/latency optimization with guardrails and observability.”
Angel Contreras
Senior Data Scientist specializing in machine learning, NLP, and MLOps
“ML/NLP engineer with experience building production-grade legal-tech and data platforms, including a GPT-4/LangChain contract review system using ElasticSearch embeddings (RAG) deployed on AWS EKS. Strong in entity resolution and scalable batch/streaming pipelines (Kafka/Spark), with measurable impact (70%+ reduction in contract review time) and a focus on monitoring and CI/CD for reliable delivery.”
Aesha Choksi
Director-level Engineering Leader specializing in Cloud Security and Data Platforms
“Engineering leader in cloud security at SysTech with player-coach experience spanning cross-team data/ownership standardization and reporting platform user-journey improvements. Stays technically deep through observability (SLA/SLOs, dashboards, alerting), rigorous code reviews (including AI-assisted coding), and end-to-end incident ownership in IAM/agentless cloud event collection. Targeting $270K–$300K base plus bonus/equity.”
Mid-level Software Engineer specializing in robotics, AI, and full-stack systems
Senior AI & Data Engineer specializing in LLM agents, RAG, and data platforms
Intern Software Engineer specializing in distributed systems and cloud infrastructure
Senior Software Engineer specializing in AI platforms for healthcare and industrial time-series ML
Senior Software Engineer specializing in cloud-native microservices and AI-enabled products
Mid-Level Software Engineer specializing in FinTech payments and risk platforms
Senior Software Engineer specializing in cloud-native SaaS and real-time collaboration
Senior Full-Stack Software Engineer specializing in cloud-native microservices and AI/LLM integration
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and real-time recommendation systems
Staff Machine Learning Engineer specializing in LLMs, recommendations, and MLOps
Senior Data Scientist specializing in AI/ML platforms for finance and healthcare
Mid-level AI/Software Engineer specializing in NLP pipelines and LLM-driven automation
Mid-level AI/ML Engineer specializing in GenAI agents and production ML systems
Director of Enterprise Analytics specializing in AI/ML for healthcare and insurance
Senior Full-Stack Python Developer specializing in cloud, data platforms, and GenAI
Mid-level Machine Learning Engineer specializing in fraud detection and recommendations