Vetted Machine Learning Professionals

“Analytics-focused candidate with experience building SQL/Python pipelines and dashboards for donor, campaign, and website performance reporting. They have worked with messy multi-source data, standardized metric definitions, and delivered automated reporting that reportedly reduced manual effort by about 80%.”

Sree Damineni

Screened

Mid AI/ML Engineer specializing in financial and insurance analytics

USA3y exp

“Senior AI/ML engineer focused on production ML, LLMs, and MLOps, with concrete experience shipping fraud detection and enterprise RAG systems. They combine strong deployment and monitoring discipline with measurable business impact, including 31% precision improvement in fraud detection and 37% better answer relevance in a financial-document QA system.”

Praveen LAKSHMAN

Screened

Mid-level Software Engineer specializing in backend systems and workflow automation

Birmingham, AL4y exp

“Early-career AI engineer currently pursuing a Master's, with hands-on experience building and improving RAG pipelines using LangChain. They stand out for moving beyond naive retrieval into multi-step retrieval and feedback-loop designs to reduce hallucinations, and are now exploring multi-agent systems with distinct retrieval, coding, and validation roles.”

Niranjaan Munuswamy

Screened

Mid-level Full-Stack Software Engineer specializing in cloud and data engineering

Chicago, IL4y exp

“Backend engineer with experience at Cigna evolving REST API services backed by PostgreSQL, emphasizing reliability/correctness, scalability, and observability. Has hands-on production experience with FastAPI (contract-first design, Pydantic schemas), performance tuning (indexes, caching), and secure auth patterns (OAuth/JWT, RBAC, row-level security via Supabase), plus low-risk incremental rollouts using feature flags and dual writes.”

“Built production AI systems for Macy's and Bloomingdale's, including an embeddings-based pipeline to clean trending search queries and an end-to-end 'Ask Macy's' multi-agent chat experience. Brings hands-on experience with real-world agent orchestration, tool integration, quality evaluation, and business-facing safeguards in a large-scale e-commerce environment.”

“Backend/platform engineer with experience across Cigna, Cognizant, and a university environment, focused on reliability, distributed systems, and regulated-domain workflows. Stands out for combining Kubernetes/Kafka/AWS infrastructure expertise with a production RAG-based healthcare compliance assistant that cut manual reporting work from 30-45 minutes to under 2 minutes while maintaining strong uptime and data-quality controls.”

Ashton Kapoor

Screened

Intern-level business analyst specializing in finance, sales, and healthcare technology

Atlanta, GA2y exp

“Sales-focused candidate with unusually broad outbound experience spanning private equity deal sourcing, merchant funding, and apartment leasing. As a student at Kalico Capital, he led a small outreach team, used PrivCo-based financial screening to target SMB/MM companies, and opened 90+ business relationships while connecting senior decision-makers to PE partners.”

Aniket Dhanawade

Screened

Mid-level Full-Stack Engineer specializing in cloud-native and AI-powered applications

USA3y exp

“Candidate has a thoughtful, hands-on approach to AI-assisted software development, treating AI as a pair programmer while retaining ownership of architecture, tradeoffs, and final code quality. They have practical experience using multi-agent workflows to ship small features end-to-end, including planning, execution, and gap detection under human oversight.”

“Software engineer who recently shipped an authentication and role-based access feature for a web app, using AI selectively for boilerplate, debugging, and test suggestions while retaining ownership of architecture, security, testing, and final review. Stands out for a disciplined, security-first approach to AI-assisted development and a pragmatic preference for lightweight API-driven solutions over unnecessary framework complexity.”

Abdur Rahman Shaik

Screened

Mid-level Front-End Software Engineer specializing in browser-based enterprise UI

Hyderabad, India4y exp

“Frontend engineer with strong ownership of complex internal tooling at Phenom, including a high-volume logging and event-trails dashboard used to debug production issues across enterprise clients like MERCK and Regions Bank. Brings a rare mix of UI architecture, browser-performance depth, and product-minded polish, with measurable impact in micro-frontend optimization, developer productivity, and enterprise adoption.”

“Full-stack engineer with experience spanning AI-powered product features and healthcare fraud detection systems. Has built end-to-end LLM-enabled applications, customer-facing recommendation systems at scale, and operational platforms that improved real-time investigations and flagged over 1,200 high-risk cases quarterly.”

“Senior Delivery Manager and former Business Analyst with broad implementation experience across AWS cloud modernization, AI-enabled healthcare workflows, CRM builds, and state-level education systems. Has worked remotely since 2011 and brings hands-on strength in discovery, stakeholder alignment, UAT, change control, and coordinating offshore delivery teams across diverse industries.”

“Currently serving as VP of Technology since January 2025, this candidate was brought in to build a fintech lending platform from the ground up, including hiring a global team and delivering a unified AI-enabled platform. They combine executive-level ownership with hands-on architecture work, including a customer-facing document agent and Plaid integration, and emphasize pragmatic AI adoption tied to measurable engineering productivity.”

“Frontend engineer who served as the main frontend contributor on a new identity verification product at Proof, building the user flow from landing page through completion. Stands out for combining reusable React/TypeScript architecture, accessibility-minded form design, and polished UX details like process-visualizing animations and loading-state cleanup.”

“Early-career/new-grad candidate who built TrendScout AI, an evidence-first market intelligence agent that ingests messy news, extracts entities/events, builds a Neo4j knowledge graph, and answers questions via RAG with citations. Achieved ~95% retrieval relevance by combining ChromaDB semantic search with graph-based retrieval and validating outputs through human evaluation and guardrails to prevent hallucinations.”

Nanyie Temlong

Screened

Director-level Product Executive specializing in enterprise SaaS, AI, and cloud modernization

Washington, DC17y exp

“Product leader focused on enterprise AI and data platform transformation, with a track record of rebuilding mission-critical analytics systems into governed, cloud-based platforms that delivered about $40M ROI. Particularly strong in trustworthy AI product design—combining governance, explainability, and human-in-the-loop workflows—and in leading cross-functional teams to ship high-impact enterprise products.”

Mayur Jain

Screened

Mid-level Full-Stack Engineer specializing in AI, blockchain, and cloud systems

Akron, OH5y exp

“Founding engineer who has built core product and backend architecture from scratch at two startups, spanning a full-stack NFT marketplace and an AI voice assistant for sales qualification and scheduling. Brings 5+ years of full-stack experience with strong React/TypeScript and Python backend depth, plus hands-on production experience with LLM workflows, evaluation, and AI-assisted developer tooling.”

Shreya Kamath

Screened

Junior Full-Stack Engineer specializing in AI-powered web platforms

San Francisco, CA2y exp

“Full-stack engineer with a strong blend of fintech and applied AI experience, having built a Stripe-based payments platform end to end and shipped an AI meeting intelligence system using LiveKit, Deepgram, and OpenAI. Particularly compelling for teams needing someone who can design reliable backend systems, productionize LLM features, and operate effectively in early-stage, ambiguous environments.”

“Electrical/embedded engineer who owned the end-to-end electronics and firmware for an ultra-portable desalination product at Nona Technologies, taking it from research concept through prototype, PCB bring-up, and iterative testing. Brings hands-on experience with harsh-environment hardware, mixed-voltage control systems, safety-critical monitoring, and designing consumer devices to be plug-and-play for non-technical users.”

Manaliben Ajudiya

Screened

Senior Software Engineer specializing in cloud, .NET, and distributed systems

Mountain View, CA11y exp

“Unity developer with unusually broad applied experience spanning real-time face recognition, AR geospatial systems enhanced with LLM-driven interactions, multiplayer networking, and cross-platform VR/mobile delivery. Also owned Honeywell Guided Work Solutions end-to-end, building server and client applications across web, Windows, and mobile for frontline worker workflows.”

“Robotics software engineer focused on multi-robot fleet orchestration in ROS 2, owning the fleet manager and task dispatch layer for pick/drop workflows. Strong in real-world reliability and safety (heartbeats, idempotent tasking, E-stop/localization confidence gates) and in debugging timing/state issues via telemetry alignment and rosbag replay, with experience in simulation, CI/CD, Docker, and Kubernetes-based deployments.”

“Robotics-focused engineer with hands-on projects ranging from a solo Dobot Magician Lite tic-tac-toe system (computer vision + minimax) to integrating an LLM with a Dobot arm for real-time pick-and-place via structured action outputs and validation. Also brings prior full-time DevOps experience (Docker/Kubernetes and CI/CD) and has used ROS/Gazebo for simulation work, including exploring improvements to crowd-aware navigation using human-trajectory datasets.”

“ML/AI engineer with healthcare payer experience (Signal Healthcare, Cigna) who has shipped production fraud/claims prediction systems using Python/TensorFlow and exposed them via FastAPI/Flask microservices integrated with EHR and Salesforce. Emphasizes operational reliability and trust—Airflow-orchestrated pipelines with data quality gates plus SHAP-based interpretability, A/B testing, and drift/debug workflows—backed by reported outcomes of 22% lower false payouts and 17% higher model accuracy.”

“Full-stack engineer with financial services experience (Lincoln Financial) who owned a customer-facing financial portal end-to-end using TypeScript/React and Node/Express. Has hands-on microservices and RabbitMQ event-driven workflows, addressing scale issues like retries/duplicates with idempotency and traceable logging, and built an internal real-time ops/support dashboard to improve monitoring and incident response.”