Vetted Machine Learning Professionals

“Financial data engineer who has built and operated high-volume batch + streaming pipelines (200–300 GB/day; 5–10k events/sec) using AWS, Spark/Delta, Airflow, Kafka, and Snowflake, with strong emphasis on data quality and reliability. Demonstrated measurable impact via 99.9% SLA adherence, major reductions in bad records/nulls, MTTR improvements, and significant latency/runtime/query performance gains; also built a distributed web-scraping system processing 5–10M records/day with anti-bot and schema-drift defenses.”

Yukta Chikate

Screened

Mid-level Machine Learning Engineer specializing in safety-critical and uncertainty-aware ML systems

Brooklyn, NY5y exp

“Built and productionized an LLM-powered assistant for company documents and support questions, focused on reducing time spent searching PDFs/policies/tickets while preventing hallucinations by grounding answers in approved sources. Demonstrates strong production engineering (Kubernetes/orchestration, caching, monitoring, fallbacks) plus security-minded permissioning and close collaboration with operations/support stakeholders.”

Anna Niedzialek

Screened

Intern Software Engineer specializing in AI/ML and computer vision

Warsaw, Poland0y exp

“Backend-focused Python engineer who owned and deployed EcoHero, a recycling guidance app using FastAPI + Firebase with barcode lookup, ZIP-code-based state rules, and user history tracking backed by 50 state datasets. Has hands-on Kubernetes + Docker experience and uses GitHub Actions and GitOps-style PR workflows for consistent deployments, plus event-driven async processing patterns with idempotency and retries.”

“Data engineer focused on AWS + Spark/Databricks pipelines, including an end-to-end nightly loan-data ingestion flow (~2.2M records) from Postgres/S3 through Glue and Databricks into a DWH with layered validation and alerting. Also built real-time streaming with Kafka + Spark Structured Streaming and a master’s project streaming Reddit data for sentiment analysis under ambiguous requirements and tight budget constraints.”

“Full-stack React/Next.js engineer focused on routing and data-fetching reliability, including handling slow/unreliable networks with loading states, retries, and request cancellation to prevent stale data. Has delivered measurable frontend performance gains (reported ~40% improvement in time-to-interactive) using lazy loading, memoization, and profiling with React Profiler.”

Muaaz Syed

Screened

Mid-level AI/ML Engineer specializing in NLP and conversational AI

Richardson, TX4y exp

“ML/NLP engineer focused on real-time IT ops analytics, building a predictive maintenance/anomaly detection platform end-to-end (multi-source ETL, streaming, modeling, and production deployment on GCP/Vertex AI). Uses deep learning (LSTMs, autoencoders/VAEs) plus embeddings (SentenceBERT) and vector search to improve incident correlation and search, citing ~40% reduction in duplicate alert noise.”

Rohan Varma Bandari

Screened

Mid-level Data Scientist & Generative AI Engineer specializing in LLMs and RAG

USA4y exp

“Built production LLM + hybrid RAG and multi-agent orchestration systems at Wells Fargo to automate complaint document/audio transcript understanding and categorization, addressing vocabulary drift via embedding + vector index updates instead of frequent retraining. Strong in LLM workflow reliability (testing/benchmarks/observability) and stakeholder-facing delivery with explainability (citations/SHAP-style justifications) and Tableau dashboards.”

Harideep Balusa

Screened

Mid-level AI/ML Engineer specializing in FinTech risk, fraud detection, and GenAI/RAG systems

USA6y exp

“Built and productionized Azure-based LLM/RAG systems for regulatory/compliance use cases, including automating analyst research and compliance report generation across large unstructured document sets. Demonstrates strong practical depth in hallucination mitigation, hybrid retrieval tuning (BM25 + embeddings), and production MLOps (Databricks, Cognitive Search, AKS, Airflow/MLflow), plus proven ability to deliver auditable, explainable solutions with non-technical compliance teams.”

Yusuf Abdikadir

Screened

Senior Software Engineer specializing in 3D simulation, digital twins, and robotics

London, United Kingdom6y exp

“UK-based Unity developer who built a 3D simulation/digital-twin platform for an autonomous-vehicle startup, integrating Unity environments with external robotics stacks, web APIs, virtual sensing, and dynamic traffic systems. Interested in moving into VR, though has not shipped VR/Meta Quest titles yet.”

“Candidate participated in Launch Factory's venture studio selection process, which introduced them to a formalized startup methodology, and then went on to found and recently exit their own business. They are highly motivated to keep building companies, with a clear emphasis on creating products that serve a community and validating market need through product-market fit.”

Cia Hang

Screened

Executive IT and Operations leader specializing in digital transformation and security

Chicago, IL13y exp

“Candidate is very familiar with the venture capital and broader investment landscape, but is not interested in founding a company. They have worked with several TPG-backed or TPG-owned organizations, helping drive business scaling, cost reduction, and execution against investor governance requirements.”

Vincent Osere

Screened

Senior Operations Analyst specializing in business intelligence and financial services

Massachusetts, USA15y exp

“Analytics-focused candidate with hands-on experience turning messy datasets into reporting-ready outputs using SQL, building reproducible Python workflows, and operationalizing metrics in R Shiny dashboards. They stand out for combining structured data analysis with NLP and segmentation in marketplace-style datasets such as Airbnb, real estate, and sports salary data to drive pricing, engagement, and demand insights.”

Adhiraj Chadha

Screened

Junior Software Engineer specializing in AI, data, and full-stack applications

Amherst, MA3y exp

“Builder with a mix of backend engineering, product instinct, and startup execution: they shipped a legal BI platform from scratch that handled 1,000+ cases, cut reporting time 80%, and saved $30K annually. They also move quickly in ambiguous environments, from launching a roommate app across iOS/Android after user discovery to building a RAG system with a 50+ case evaluation suite and a cloud dev environment in under 48 hours.”

“Engineer with hands-on experience designing and leading multi-agent AI development workflows, including a LangGraph-based system that automated parts of a RAG pipeline and significantly reduced development time. Stands out for treating AI agents like an engineering team, with clear architecture, handoff schemas, validation, and supervisor-driven conflict resolution.”

Chinmay Warang

Screened

Senior Audio Software Engineer specializing in real-time audio ML systems

Somerville, MA5y exp

“Startup backend engineer with unusually deep end-to-end ownership of real-time audio/ML systems. At Modulate, they rebuilt the core Audio Intelligence API used by enterprise customers like Activision, cutting latency 70% and eliminating session loss, and also independently created a data labeling platform that powered the company’s model training during a major product pivot.”

“Backend engineer who built an AI-powered grant matchmaking platform for researchers and professors, combining semantic matching, embeddings, and Semantic Scholar enrichment with rule-based eligibility filters. Stands out for pragmatic AI engineering: they focused on reliability through confidence scoring, logging, manual validation, and production-minded backend design.”

“Education strategy and product leader with deep math education expertise who helped transform a literacy/assessment-focused company into a more comprehensive, integrated math solutions provider. Particularly strong at embedding AI-driven insights into teacher workflows in a human-centered way, balancing personalization, usability, teacher autonomy, and educational equity.”

“Backend-focused engineer with strong Go and database optimization experience who improved a high-traffic API by about 30% and helped stabilize peak-load performance for an event reservation platform. Brings hands-on production experience across PostgreSQL, Redis, Rails/Go services, and B2B SaaS integrations with Slack, Hubstaff, and RingCentral, with a clear pattern of owning performance bottlenecks end to end.”

“Full-stack Python engineer who has owned internal automation products from requirements through production, including a financial reporting platform that improved deployment time by 45% and raised reporting efficiency to 98%. Also built an AI-powered movie recommendation engine using collaborative and content-based filtering, with hands-on experience across frontend, backend, data pipelines, and ML evaluation.”

“Built an end-to-end automated trading system for Polymarket, including Go/Python execution services, Terraform-scheduled ETL/feature pipelines, and monitoring on modest hardware. Also shipped a production LLM+RAG signal verifier/explainer that grounds trade decisions in external context (news/social) with vector DB retrieval and guardrails, plus a lightweight RAGAS-style eval loop on ~50 resolved markets that improved signal faithfulness by ~15%.”

Anthony Tilotta

Screened

Senior Developer Advocate specializing in Web3 and API platforms

Remote, USA9y exp

“Seasoned AI developer advocate with 8 years of experience translating complex engineering concepts into developer-friendly content and workflows. Built an open source repository that gives AI agents structured API knowledge, which the candidate says drove a 55% increase in API adoption and reduced support tickets. Currently at Moralis, combining API implementation support, LLM tuning, and developer education across video, documentation, and hands-on guidance.”

“Engineering director and hands-on architecture leader who combines people management with strong systems design depth across performance optimization, serverless event-driven platforms, and developer-facing AI tooling. Notable wins include cutting API latency 30%, reducing shipping time 20%, and refactoring a product into a Claude Code-native workflow optimized for token efficiency and developer context management.”

“Backend engineer who architected and owned a mission-critical outage management/decision-support platform, replacing a legacy system that failed under load. Emphasizes auditability, deterministic validation, and server-side concurrency controls (section locking, scoped autosaves), plus redundancy/load balancing and monitoring to keep the system stable for 24/7 operations handling 1,500+ weekly outage events.”