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Vetted CSS Professionals

Pre-screened and vetted.

DP

Entry-Level Full-Stack Software Engineer specializing in AI agents and cloud-native apps

1y exp
ScriptsHub TechnologiesUniversity of Cincinnati
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AF

Junior Engineering Technician specializing in product development, CAD, and robotics

Thorofare, NJ2y exp
TroemnerPenn State University
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SK

Mid-level Full-Stack Software Engineer specializing in cloud, microservices, and AI integration

Harrison, NJ4y exp
One CommunityNJIT
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YP

Mid-level Software Engineer specializing in backend systems, APIs, and cloud microservices

TX, USA4y exp
DXC TechnologyTexas A&M University
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AU

Senior Data Scientist and Machine Learning Researcher specializing in NLP, LLMs, and MLOps

Lubbock, TX9y exp
Texas Tech UniversityTexas Tech University
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UJ

Mid-level UX Designer specializing in AI-powered, accessible, motion-driven experiences

California, United States6y exp
Shaka WearCollege for Creative Studies
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RG

Mid-level Product Designer specializing in accessible FinTech and Healthcare UX

Dallas, TX5y exp
FBS SecuritiesIUPUI
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AS

Intern Full-Stack Software Engineer specializing in AI integrations and cloud-native web apps

California, United States2y exp
Moblize.ITIllinois Institute of Technology
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IB

Junior Software Engineer specializing in backend, microservices, and cloud

San Francisco, CA2y exp
KarmeqSyracuse University
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PP

Junior Full-Stack Developer specializing in React, Node.js, and AWS

St. Louis, MO3y exp
Saint Louis UniversitySaint Louis University
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RM

Senior Software QA Engineer specializing in test automation and API validation

10y exp
Education DynamicsUC Santa Cruz
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SK

Senior Full-Stack & Cloud Engineer specializing in AWS Serverless SaaS

9y exp
Republic Services
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AZ

Senior Full-Stack Software Engineer specializing in Python, React, and LLM-powered applications

Woodbridge, Virginia, US7y exp
HealthEdge
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HK

Himanshu Kiran Garud

Screened ReferencesStrong rec.

Mid-Level Software Engineer specializing in full-stack web and data engineering

United States4y exp
EPRIUniversity of North Carolina at Charlotte

Backend/ML engineer who has built both enterprise data pipelines and real-time AI products: modular Python (Flask/FastAPI) services integrating automation scripts and low-latency ML inference (MediaPipe, PyTorch) plus OpenAI-powered feedback. Demonstrated measurable performance wins (~30% faster HR workflows; ~40% faster AWS pipelines across 100+ Oscar Health feeds) and strong multi-tenant/data-isolation patterns (schema-based isolation, RBAC, microservices).

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RG

Rithiwik Garuda

Screened ReferencesStrong rec.

Mid-level Full-Stack Engineer specializing in cloud-native, event-driven data platforms

5y exp
InfosysUniversity of New Haven

Backend/data engineer with hands-on production experience building Python (FastAPI/Flask) data enrichment services secured with Okta OAuth2 and monitored via Splunk/Dynatrace. Has delivered AWS event-driven and data-migration solutions (Lambda + Kafka to EKS; Glue from on-prem Oracle to S3/data lake) and modernized Informatica match/merge logic to cloud services using parallel-run parity validation and stakeholder sign-off.

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PR

Priyanka Ramesh

Screened ReferencesStrong rec.

Junior Full-Stack Software Engineer specializing in Java/Spring Boot and React

Boston, MA2y exp
IpserLabNortheastern University

Backend engineer (IpserLab) who owned Python services for a production quiz/analytics platform, focusing on reliability and low-latency behavior under peak load. Hands-on with Kubernetes + Docker deployments and GitHub Actions CI/CD in a GitOps-style workflow, including solving configuration drift and enabling fast rollbacks. Also implemented Kafka-based event streaming with idempotent consumers and strong observability (lag tracking, structured logging, alerting).

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TA

Tanweer Ashif

Screened ReferencesStrong rec.

Mid-level AI/ML Engineer and Data Scientist specializing in LLMs and MLOps

Buffalo, NY5y exp
University at BuffaloUniversity at Buffalo

Data science/AI intern at University at Buffalo Business Services who built and deployed production systems spanning classic ML and LLM assistants. Delivered real-time competitor intelligence for a Cornell-partnered, $1B beverage launch by scraping/cleaning 5,000+ SKUs and deploying models via API, then built a domain-aware LLM assistant to modernize Excel-based workflows with strong grounding, privacy controls, and sub-5s latency.

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