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Vetted Random Forest Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in GenAI, RAG, and cloud-native ML platforms
Mid-level AI/ML Engineer specializing in recommender systems, NLP, and MLOps
Mid-level Full-Stack Developer specializing in .NET, Python/Django, and cloud-native web apps
Mid-level Software Engineer specializing in event-driven backend and on-device ML for robotics
Mid-level AI/ML Engineer specializing in NLP, RAG, and agentic AI
Mid-level AI Data Scientist specializing in financial risk, fraud detection, and NLP/LLM systems
Intern Software Engineer specializing in distributed systems and FinTech
Mid-level Data Scientist specializing in marketing analytics and scalable data platforms
Senior Data Scientist specializing in Generative AI, NLP, and MLOps
Longyang Xu
Junior Full-Stack Software Engineer specializing in cloud microservices and ML-driven products
“Backend engineer with hands-on ownership of Python/Flask microservices and recommendation systems across edtech and telecom. Deployed and operated real-time personalization/recommendation platforms on AWS EKS with Jenkins-based CI/CD, GitOps-style declarative configs, and strong observability practices. Has migration experience moving legacy mixed environments to modern containerized Kubernetes and built Kafka pipelines feeding ML services while managing schema evolution.”
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.”
Syed Daim Ali
Intern Software Engineer specializing in FinTech and AI platforms
“Systems-focused engineer who built an OS kernel with multithreading, priority scheduling, system calls, and synchronization primitives, and debugged race conditions end-to-end. While not yet hands-on with ROS/SLAM, they clearly connect low-level concurrency and scheduling decisions to deterministic, reliable robotics-style real-time workloads.”
Priyanshu Maurya
Mid-level Data Scientist specializing in insurance, finance, and healthcare analytics
“Built and productionized LLM-driven sentiment scoring for earnings call transcripts at Goldman Sachs, replacing legacy NLP to deliver a cleaner trading signal while managing latency/cost via batching, caching, and distilled models. Also implemented an Airflow-orchestrated fraud modeling pipeline at MetLife with drift-based retraining and SageMaker deployment, and has a disciplined evaluation/rollout framework for reliable AI workflows.”
Staff Machine Learning Engineer specializing in LLM agents and ML systems
Mid-level Data Scientist specializing in machine learning, analytics, and cloud data pipelines
Mid-level Full-Stack Engineer specializing in cloud DevOps and LLM applications
Mid-level Data Scientist specializing in ML, MLOps, and forecasting for FinTech and AI hardware
Intern AI/Data Science Engineer specializing in LLM agents, data engineering, and predictive analytics