Vetted Feature Engineering Professionals

Pre-screened and vetted.

WW

Mid-level Software Engineer specializing in FinTech data pipelines and backend systems

Midtown, NY3y exp
QundamentalNYU
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AA

Junior Data & AI Analyst specializing in BI, LLM applications, and analytics

California, United States1y exp
EYSanta Clara University
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SL

Senior Data Engineer specializing in cloud lakehouse platforms for banking and healthcare

Dallas, TX6y exp
U.S. BankIndiana Wesleyan University
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SS

Mid-level Data Engineer specializing in cloud data platforms and BI analytics

Remote, USA4y exp
U.S. BankSan José State University
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AS

Mid-level Data Engineer specializing in cloud lakehouse and streaming analytics for financial services

New York, NY3y exp
AccentureUniversity of Alabama at Birmingham
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MK

Mid-level Data Engineer specializing in cloud data pipelines and analytics (AWS/Azure)

Fairfax, VA4y exp
AllstateGeorge Mason University
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BG

Mid-level Data Engineer specializing in cloud ETL, streaming, and ML-ready data pipelines

Boise, ID5y exp
AlbertsonsTexas State University
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CG

Mid-level AI/ML Engineer specializing in cloud MLOps, LLM agents, and risk & fraud modeling

5y exp
CNA FinancialUniversity of Dayton
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SB

Mid-level Data Engineer specializing in big data pipelines and cloud data platforms

Dallas, TX6y exp
HoneywellEast Texas A&M University
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GG

Mid-level Business Intelligence Engineer specializing in AI-powered analytics

New York, NY3y exp
LTIMindtreeWright State University
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MC

Senior Data Scientist specializing in ML engineering and cloud analytics

Calgary, Canada8y exp
Geek Inc.Georgia Tech
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TS

Mid-level AI/ML Engineer specializing in generative AI and cloud ML platforms

Remote4y exp
HCA HealthcareUniversity of Memphis
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SN

Mid-level AI Engineer specializing in LLMs, RAG, and multi-agent systems

Dallas, TX5y exp
JLLStevens Institute of Technology
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BR

Mid-level Software Engineer specializing in AI-driven full-stack systems

United States3y exp
Capital OneUniversity of Central Missouri
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JV

Mid-level AI Engineer specializing in machine learning and generative AI

New York, NY5y exp
USAAYeshiva University
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KG

Mid-level Founding Engineer specializing in GenAI and FinTech

New Brunswick, NJ5y exp
Aarohaa AIRutgers University
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KC

Senior AI/ML Engineer specializing in MLOps and Generative AI (LLMs/RAG)

Chicago, IL10y exp
United Airlines
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VS

Mid-level Applied AI Engineer specializing in Generative AI and RAG systems

Dallas, Texas5y exp
AT&T
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PM

Mid-level Data Scientist specializing in ML, NLP, and LLM-powered analytics

Westlake, OH4y exp
KeyBank
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BR

Bharath Reddy Nallu

Screened ReferencesStrong rec.

Mid-level Machine Learning Engineer specializing in NLP and scalable MLOps

4y exp
Northern TrustUniversity of the Cumberlands

Data/ML engineer in financial services (Northern Trust) who built a production RAG-based LLM system to connect structured transaction/portfolio data with unstructured market and internal documents for risk teams. Strong in end-to-end pipelines (AWS Glue/Airflow/PySpark), entity resolution, and taking models from prototype to reliable daily production with performance tuning (LoRA + TensorRT) and monitoring.

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Ashutosh Khatavkar - Mid-level SDET/Software Engineer specializing in test automation and CI/CD in Syracuse, NY

Ashutosh Khatavkar

Screened ReferencesStrong rec.

Mid-level SDET/Software Engineer specializing in test automation and CI/CD

Syracuse, NY3y exp
UbisoftSyracuse University

AAA game QA professional from Ubisoft (For Honor) with deep live-service multiplayer experience. Known for owning network/competitive integrity risks and building a custom network simulation tool to reliably reproduce desync issues, accelerating debugging and saving 100+ hours. Strong end-to-end QA process skills spanning test planning, triage, regression, and release verification using JIRA/TestRail.

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AV

Anju Vilashni Nandhakumar

Screened ReferencesStrong rec.

Entry-level Machine Learning Engineer specializing in RAG and NLP systems

Boston, MA1y exp
Community Dreams FoundationNortheastern University

Built a 24/7 Python/LangChain email agent in production with validation, circuit breakers, human-review escalation, and structured observability. Also applied data and automation skills at Community Dreams Foundation, including turning a vague donor-insights request into a usable donor-risk prediction workflow and raising ETL reliability from roughly 85% to 99% by diagnosing SQLite concurrency issues.

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