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Vetted Random Forest Professionals
Pre-screened and vetted.
Entry-Level Data Scientist specializing in Applied Analytics and Machine Learning
Intern Data Scientist specializing in LLMs, RAG, and data engineering
Mid-level Data Scientist specializing in GenAI, NLP, and deep learning
Junior Software Engineer specializing in Trust & Safety, QA automation, and ML
Mid-level Machine Learning Engineer specializing in NLP, federated learning, and fraud detection
Mid-level Data Scientist specializing in GenAI, NLP, and deep learning
Mid-level Machine Learning Engineer specializing in recommender systems and LLM/RAG pipelines
Mid-level AI/ML Engineer specializing in GenAI, LLMs, and RAG pipelines
Senior Solutions Architect specializing in cloud infrastructure, AI/LLM security, and data platforms
Mid-level AI/ML Engineer specializing in multimodal and generative AI at scale
Mid-level Full-Stack Developer specializing in cloud-native apps, AI/ML, and microservices
Intern AI Software Engineer specializing in LLM inference optimization and model compression
Junior Robotics & AI Engineer specializing in autonomous systems and machine learning
Mid AI/ML Engineer specializing in LLM systems and inference optimization
Senior AI Infrastructure & Backend Engineer specializing in LLM systems
Senior AI Infrastructure Engineer specializing in LLM systems and real-time ML platforms
Sanketh Reddy
Senior Data Engineer specializing in cloud data platforms and large-scale ETL
“Data engineer focused on large-scale ETL/ELT pipelines across cloud stacks (GCP and AWS), including Spark-based transformations and orchestration with Airflow. Has experience loading up to ~2TB per BigQuery target table and designing atomic loads to multiple downstream systems (Elasticsearch + Kafka), with Kubernetes deployment and Jenkins CI/CD.”
Abhay Murjani
Director-level Data Science Manager specializing in ML forecasting, experimentation, and MLOps
“Data/ML engineer with experience at American Express and Amazon, owning an end-to-end rewards redemption/liability ML pipeline (~200GB) with rigorous regulatory/audit validation and quarterly executive reporting. Also built web-scraped product datasets with anti-bot protections at a startup and helped modernize an authn/authz service using AWS, plus led early-stage migration work from an internal warehouse to GCP with CI/CD and cloud observability.”
grusha shetty
Senior Data Analyst specializing in product analytics and experimentation
“Analytics candidate with strong product and growth analytics experience across SQL, Spark, Python, and Tableau. They have built clickstream funnel pipelines, automated Bayesian experiment evaluation, and used Markov chain journey modeling to uncover onboarding friction that led to a 5% conversion improvement. They also show strong cross-functional influence by standardizing churn definitions across product and marketing teams and operationalizing adoption in shared dashboards.”