Vetted R Professionals

“AI/ML engineer who has deployed production LLM/transformer-based systems for merchant intelligence and fraud/support optimization, delivering +27% merchant engagement and +18% payment success. Deep experience in privacy-preserving, PCI DSS-compliant data/ML pipelines (Airflow, AWS Glue, Spark, Delta Lake) and scalable microservices on Kubernetes, plus proven cross-functional delivery in healthcare claims analytics at UnitedHealth Group (12% HEDIS claim reduction).”

“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

Screened

Director-level Data Science Manager specializing in ML forecasting, experimentation, and MLOps

New York, NY6y exp

“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.”

“Backend/AI systems engineer who has shipped production LLM agents focused on prompt engineering, code generation, and incident-response automation. Stands out for combining strong agent orchestration and reliability engineering with measurable business impact, including 60-70% cost reductions, 45% lower monthly LLM spend, and a 5x increase in developer iteration speed.”

Alexander Smith

Screened

Junior Software Engineer and Data Scientist specializing in AI/ML systems

California, USA3y exp

“Built production-grade automation and ML/data pipelines at Dun & Bradstreet and ThreadNotion, spanning large-scale document classification, country risk report automation, and resilient Playwright testing for dynamic AI chat workflows. Particularly strong in turning brittle or ambiguous systems into reliable, observable, end-to-end automated platforms.”

Tanay Bali

Screened

Intern-level quantitative analyst and researcher specializing in quantum science and risk modeling

Rome, NY7y exp

“Quantitative builder with a physics and applied math background who has turned complex simulation and risk models into usable visualization tools for finance and insurance teams. Built Monte Carlo portfolio dashboards at DGI and geospatial natural-disaster risk visualizations at Tiger Risk, with evidence of organic adoption in decision-making and client presentations.”

Jianing Gu

Screened

Junior Digital Marketing Specialist specializing in social media growth and performance marketing

Los Angeles, CA2y exp

“Growth-creative marketer with hands-on paid social and short-form video experience across restaurant and beauty (Tom Ford Beauty). Runs structured creative experiments (Meta A/B ad sets, Meta Pixel conversion tracking) and adapts strategy to platform behaviors (TikTok comments vs IG sharing). Has led creators/editors and drove a reported 100% ROAS lift on a Valentine’s Day TikTok ads iteration.”

Jeff Zhou

Screened

Senior strategy and operations leader specializing in product, M&A, and growth strategy

New York, NY10y exp

“Strategy and corporate development leader with a rare mix of big-company M&A experience at Indeed, private equity training, and hands-on founder experience. They have advised leadership on inorganic growth in HR tech, helped take a job seeker product from market research to launch and monetization, and built a mentor-mentee marketplace for international students in New York.”

“BlackRock application engineer/product owner focused on enterprise AI platforms, building internal GenAI and ML workflow products for operations and business teams. Stands out for combining consultative solution design with hands-on implementation, including a contract review platform that cut first-draft review time by 60%+ and an AI mailbox tool that drew interest from 17 additional teams during the POC stage.”

kirandeep virdi

Screened

Executive HR leader specializing in transformation, talent, and people analytics

New York, USA13y exp

“Startup operator who joined Asper.ai at the pre-product, pre-revenue stage as Head of HR and helped scale it over 3.6 years to 180+ employees, 5 global locations, $10M ARR, and a $20M Series A. Unusually broad in scope, they combined people leadership with marketing, global expansion, financial governance, brand launch execution, and M&A-related HR work.”

“ML/AI engineer focused on production-grade model reliability: built a monitoring and validation framework to detect drift, trigger anomaly alerts/retraining, and maintain consistent performance for device intelligence workflows at scale. Strong MLOps background with Python pipelines, Docker/Kubernetes deployments, Airflow orchestration, and real-time monitoring dashboards; experienced partnering with product managers to deliver business-facing insights.”

“Candidate mentioned working in a GTM role at Swing Phi, supporting cross-functional efforts around customer segmentation, profiling, and sales pipeline targeting. They cited using Python, SQL, and Excel for data analysis and attributed a 5% increase in acquisition rate to this work.”

“Robotics-focused candidate who built core software for a ROS2 pick-and-place arm that sorted colored cubes using an overhead camera and an AI color-recognition model. They owned arm modeling in ROS, motion logic (coordinate-to-IK-to-joint paths), and created a data-driven linear error-correction calibration to mitigate camera/AI coordinate bias, plus tuned motion speed to improve real-world repeatability.”

“AI engineer at Anote.ai who built and shipped a production multi-agent LangGraph/LangChain/Ray RAG platform for enterprise search and workflow automation, supporting 3 commercial products and 100+ developers. Drove measurable gains (30% accuracy improvement, lower latency) and improved reliability with Redis-based state checkpointing, message-queue synchronization, and Milvus retrieval optimizations, while partnering with PMs/clients to add transparency features like confidence scores and real-time logs.”

Akhilaa Sonduri

Screened

Junior Full-Stack Software Engineer specializing in SaaS and AI-powered web apps

Cambridge, MA2y exp

“Full-stack engineer with experience at HubSpot, Accolite, and an early-stage USC alumni startup (Workup). Built and shipped end-to-end workflow automation features (dynamic input configuration with strict schema validation) driving ~25% faster configuration, and delivered an AI interview customization feature in a high-ambiguity startup setting that increased adoption by ~40%. Comfortable operating production systems on AWS with CloudWatch observability and CI/CD, and has built real-time web apps with caching/indexing for performance.”

Shanay Wadhwani

Screened

Mid-level Data Scientist specializing in NLP, computer vision, and applied ML

Washington, DC6y exp

“AI/ML engineer with impactful work for the World Bank across both LLM systems and computer vision, including a PRAI evaluator-assistance platform and a production UNet model for slum detection from multispectral satellite imagery. Earlier built multilingual NLP-based borrower segmentation and credit scoring at Creditmate through its acquisition by Paytm, showing strong experience in ambiguous, high-impact environments.”

“Candidate brings a mix of business development and investment-style diligence experience across a crypto startup, healthcare software analysis, and US market-entry work. They have built outbound pipelines from scratch, supported diligence by benchmarking metrics and surfacing risks, and synthesized customer and market insights into actionable updates for senior teams.”

“Engineer with hands-on experience shipping production Python integrations and designing for reliability from day one, including idempotency, retries, dead-letter handling, contract checks, and full observability. Also brings web automation experience with Puppeteer and has implemented high-availability failover using load balancer liveness checks, backup environments, and cold standby architecture.”

“Primary engineer at Customer Insights AI who built an end-to-end Python pipeline for 340B drug pricing compliance, using ML to detect suspicious pharmaceutical claims and benefit diversion. Stands out for combining healthcare compliance domain knowledge with production reliability practices, and for turning ambiguous analyst-driven review processes into automated workflows that cut manual review by 70%.”

“Internship experience at TikTok and nCino, with hands-on work spanning production Python data pipelines, recommendation-system feature workflows, Salesforce Apex automation, and flaky UI automation for a live stock recommendation platform. Stands out for a reliability-focused approach: anticipating failure modes, instrumenting observability, and turning ambiguous business processes into maintainable automated systems.”

“Postdoctoral/PhD researcher focused on Alzheimer's disease who has built scalable end-to-end AI systems across pathology imaging, transcriptomics, and longitudinal neuroimaging. Particularly strong in turning novel research ideas into robust Python pipelines on GPU/HPC infrastructure, with pathologist-facing impact and scientifically novel findings such as image-derived disease severity trajectories and subtype discovery.”