Vetted Machine Learning Professionals

Pre-screened and vetted.

Sragvi Vadali - Junior Software Engineer specializing in AI/ML and real-time systems

Sragvi Vadali

Screened

Junior Software Engineer specializing in AI/ML and real-time systems

2y exp
University of Southern CaliforniaUSC

Backend/AI engineer who built a real-time vector database system for high-frequency financial data using Kafka/Flink on Kubernetes, achieving sub-100ms similarity search at 10k+ concurrent load and resolving tricky duplication issues with idempotency/versioning. Also shipped an end-to-end LLM-based travel itinerary feature (profiling + prompt workflows + APIs) with a focus on quality consistency and low latency.

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Sai Charan Kolla - Mid-level AI/ML Engineer specializing in LLMs, RAG, and MLOps on AWS in TX, USA

Mid-level AI/ML Engineer specializing in LLMs, RAG, and MLOps on AWS

TX, USA5y exp
BlackRockTexas A&M University-Kingsville

LLM engineer who built a production document intelligence/RAG pipeline to extract structured data from thousands of unstructured PDFs, cutting manual review time by 60%. Experienced with LangChain and Airflow orchestration plus rigorous evaluation (labeled datasets, prompt testing, HITL review, monitoring) to improve accuracy and reduce hallucinations while partnering closely with non-technical operations stakeholders.

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Hari Chandana Kasula - Entry Machine Learning Engineer specializing in NLP, computer vision, and recommender systems in New York, NY

Entry Machine Learning Engineer specializing in NLP, computer vision, and recommender systems

New York, NY0y exp
Columbia UniversityColumbia University

Built and shipped an end-to-end podcast recommendation system exposed via a Flask API and React UI, explicitly balancing relevance, diversity (MMR), and safety constraints while meeting ~200ms latency targets. Also implemented a production-style RAG/information-extraction pipeline using web retrieval, spaCy NER, and fine-tuned SpanBERT with guardrails and evaluation loops (precision/recall/F1) to tune confidence thresholds and improve reliability.

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Dhyey Desai - Intern AI/ML Engineer specializing in RAG, multimodal AI, and LLM systems in Los Angeles, California

Dhyey Desai

Screened

Intern AI/ML Engineer specializing in RAG, multimodal AI, and LLM systems

Los Angeles, California0y exp
NalaUSC

Built and shipped 'PetPulse,' a production AI pet-health note system that records voice notes, transcribes them, converts transcripts into structured symptom/event data, and supports grounded Q&A over a user’s notes and vet PDFs. Demonstrates full-stack LLM product execution (FastAPI + GPT-4 + Firebase), with concrete reliability/performance work (async endpoints, caching, RAG/embeddings, function calling) and user-centered iteration with a non-technical product stakeholder.

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Zuocheng Li - Entry-Level Software Engineer specializing in full-stack web and Android development in San Jose, CA

Zuocheng Li

Screened

Entry-Level Software Engineer specializing in full-stack web and Android development

San Jose, CA0y exp
San José State UniversityUSC

Early-career developer whose experience comes from classroom projects but has completed full end-to-end web app delivery: implemented login/search/favorites, integrated external APIs, and deployed to Google Cloud for multi-device use. Demonstrates user-centered iteration by recruiting friends to test and provide feedback, and has hands-on production-style debugging experience (e.g., resolving CORS issues during deployment).

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Divyam Agrawal - Mid-level Machine Learning Engineer specializing in LLMs and NLP classification systems in Seattle, WA

Mid-level Machine Learning Engineer specializing in LLMs and NLP classification systems

Seattle, WA4y exp
Affinity SolutionsUniversity of Washington

Internship experience building a production RAG+LLM pipeline to map messy card transaction descriptions to merchant brands, including a custom modified-ROUGE evaluation approach for weak/variant ground truth. Improved scalability and cost by moving from a managed LLM endpoint (e.g., Bedrock) to self-hosted vLLM, and orchestrated massive embedding backfills (5,000+ files, 10B+ rows) using an Airflow-triggered SQS + ECS worker architecture with robust retry/DLQ handling.

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TS

Mid-Level Full-Stack .NET Developer specializing in cloud microservices and data pipelines

6y exp
Elevance HealthMissouri State University

Backend/data engineer with experience at Citi and Elevance Health, building end-to-end pipelines and data services in regulated, high-volume environments. They combine Python, SQL, .NET, Azure Functions, and strong observability/reliability patterns to improve processing speed, reduce manual effort, and maintain high uptime across financial and healthcare data platforms.

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JC

Senior Engineering Manager specializing in software platforms, AI, and FinTech

Houston, TX12y exp
ThetaColorado School of Mines

Entrepreneur building a luxury rental car company startup with capital already raised, though undisclosed. Demonstrates a thoughtful founder mindset centered on vision, growth trajectory, due diligence, and market penetration, and is actively building connections in the VC/accelerator ecosystem.

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ST

Director-level telecom standards leader specializing in 3GPP, 5G/6G architecture, and AI-driven networks

Chicago Area, IL23y exp
SIXTH-LOGIC ADVISORYOklahoma State University

Telecommunications strategist with more than two decades of experience spanning 3G through emerging 6G, focused on shaping global standards and advising senior leadership. Created a global AI-enabled autonomous systems framework in NGMN, has multiple patents in telecom, and is particularly differentiated by his ability to represent company interests in 3GPP while driving interoperable, multi-vendor 6G ecosystems.

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SG

Shilpa Ghosh

Screened

Senior Business Analyst specializing in financial and research analytics

Santa Clara, CA7y exp
University at BuffaloUniversity at Buffalo

Analytics professional with experience spanning HSBC and the University of Buffalo, combining banking risk/portfolio analytics with reproducible Python and SQL reporting workflows. Stands out for cleaning complex multi-source data, standardizing business metrics across dashboards, and delivering measurable impact including an 80% reduction in manual reporting and an estimated GBP 1.2M profit contribution from scorecard redevelopment.

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Amaan Elahi - Mid-level Software Engineer specializing in backend, AI, and full-stack systems in New York, NY

Amaan Elahi

Screened

Mid-level Software Engineer specializing in backend, AI, and full-stack systems

New York, NY5y exp
SAIL GTXNYU

Built and shipped production LLM agents including an internal RAG-based compliance classification system at SAIL (FastAPI/Redis/Docker) designed to handle real failure modes and scale to ~10k LLM calls/hour, achieving ~93% pipeline accuracy with reduced hallucination risk via multi-model orchestration and strict grounding. Also architected “Elara,” a state-machine-driven conversational appointment booking agent using structured JSON outputs and backend function execution for reliability, and has experience normalizing messy OTA/PMS data at RateGain.

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Pahuldeep Singh - Senior Full-Stack Developer specializing in scalable web platforms and automation in Remote

Senior Full-Stack Developer specializing in scalable web platforms and automation

Remote6y exp
CalianGeorgia Tech

Backend/full-stack engineer focused on TypeScript/Node.js systems, with hands-on ownership of a real-time telemetry and dashboard platform built on Kafka, Debezium, PostgreSQL, and GraphQL. Stands out for combining event-driven architecture, correctness/idempotency patterns, strong observability, multi-tenant security, and developer-friendly API design in production environments.

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Chanatip Vachirathanusorn - Entry-level Software Engineer specializing in full-stack and FinTech systems in San Diego, CA

Entry-level Software Engineer specializing in full-stack and FinTech systems

San Diego, CA2y exp
AppFolioUC San Diego

Software engineer with AppFolio payments experience who shipped an end-to-end payment adoption rollout during a short internship, including full-stack implementation, stakeholder coordination, and real-time monitoring. Also built an insurance service AI agent inspired by his father's agency, combining structured document ingestion, RAG, and agentic integrations to improve reliability on dense policy documents.

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TS

Tyler Shimizu

Screened

Junior Software Engineer specializing in full-stack web development

Berkeley, CA2y exp
University of California, BerkeleyUC Berkeley

Built a Flask-based web application for NCAA Men's gymnastics and also worked on a survey-question collection and normalization project for UC Berkeley's Cameron Institute. Shows a clear reliability mindset through validation, testing, logging, and error handling, and is comfortable turning ambiguous, messy data workflows into stable applications.

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Anirban Ghosh - Mid-level Machine Learning Engineer specializing in data science and cloud systems in Seattle, WA

Anirban Ghosh

Screened

Mid-level Machine Learning Engineer specializing in data science and cloud systems

Seattle, WA4y exp
AmazonStony Brook University

ML engineer who independently pitched and built a recommendation engine at Danske Bank in a legacy fintech environment, creating compliant data pipelines and deployment infrastructure from scratch and delivering a 62% engagement lift with 70%+ advisor adoption. Also worked at AWS on classification and GenAI-powered reporting systems, with strengths spanning production ML, platform setup, monitoring, and research-to-production optimization.

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JY

Jing Yang

Screened

Senior Machine Learning Engineer specializing in NLP and generative AI

McLean, VA8y exp
Capital OneUniversity of Utah

ML/AI engineer focused on production NLP and voice AI systems in the restaurant tech space, with hands-on work spanning ASR, intent classification, LLM fine-tuning, and deployment monitoring at Presto AI. They highlight a 15% improvement in full-AI ordering rate and also built a restaurant sentiment analysis product at Wisely that they say became a standout feature in a $10M acquisition context.

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Sergio Nunez - Senior Unity Engineer specializing in XR, mobile, and AI avatar experiences in Los Angeles, CA

Sergio Nunez

Screened

Senior Unity Engineer specializing in XR, mobile, and AI avatar experiences

Los Angeles, CA9y exp
GeniesCETYS University

Unity/C# game engineer from Genies who built the avatar wearable customization system for Silver Studio and supported AI companion features through client-side LLM integrations. Stands out for combining clean architecture, analytics-driven product thinking, and practical optimization work across latency, AI cost controls, and mobile performance.

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Sachin Komati - Mid-level AI/ML Engineer specializing in GenAI, RAG, and healthcare ML in Florida, USA

Sachin Komati

Screened

Mid-level AI/ML Engineer specializing in GenAI, RAG, and healthcare ML

Florida, USA5y exp
BlackRockFlorida International University

Built an end-to-end GenAI/RAG platform for financial compliance and research at BlackRock, focused on safe, auditable answers in a highly regulated environment. Combines strong LLM engineering depth with production platform skills and delivered clear business impact, including reducing research/compliance turnaround from hours to seconds, improving retrieval relevance by 22%, and cutting inference costs by 75%.

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Farhan Shahbaz - Senior Software Engineer specializing in cloud infrastructure and platform engineering in New York, NY

Senior Software Engineer specializing in cloud infrastructure and platform engineering

New York, NY4y exp
JPMorgan ChaseWest Virginia University

Backend engineer with deep experience in security and access-management platforms at JPMorgan Chase, including owning automation for migrating 50+ engineering teams from CyberArk to HashiCorp Vault. Stands out for combining regulated-environment rigor, infrastructure automation, and production operations with practical AI integration in internal access workflows.

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MS

Mihir Sahu

Screened

Intern software engineer specializing in AI, full-stack, and applied ML

Madison, WI1y exp
Capital OneUniversity of Wisconsin–Madison

Backend/ML-focused engineer with experience spanning fintech, sales enablement, and medtech, including a Capital One capstone and a Singapore medtech startup internship. Stands out for owning end-to-end AI/backend systems, from a GenAI sales pitch platform that cut prep time by 50% to an ultrasound-guidance MVP for non-expert operators in a highly ambiguous domain.

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SZ

Director of Software Engineering specializing in platform modernization and enterprise systems

Austin, TX24y exp
ClearAjnaGovernors State University

Engineering leader with experience owning product engineering strategy, architecture, and org scaling across hospitality/workforce management and insurance startup environments. They describe being brought in to help Fourth Inc. revamp engineering for large-scale enterprise customers, while also scaling teams at The Zebra and staying hands-on with production monitoring, performance analysis, and cross-team architectural execution.

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MK

Senior Software Engineer specializing in data visualization and full-stack web apps

San Francisco, CA15y exp
TrialTraceUniversity of Florida

Frontend-focused product engineer from TrialTrace who owned features end-to-end across product decisions, architecture, implementation, and testing. Strong in TypeScript/React applications with complex data visualization and dashboarding, including refactoring core coordinate logic, building filter-state architecture, and shipping fast user-driven features.

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MT

Mikko Tormala

Screened

Director of Software Engineering specializing in AI-native full-stack product engineering

Los Angeles, CA25y exp
SiemensMetropolia University of Applied Sciences

Engineering director and former front-end engineering manager with a strong blend of people leadership, UX/design-system ownership, and hands-on technical depth. At Siemens, they led a 15-person US/Europe team through a SaaS-era design-system transformation, winning over resistant product teams and exceeding adoption goals; at Intellimize, they solved legacy-browser constraints with a custom TypeScript-based build pipeline that improved quality, morale, and user experience.

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