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Vetted Data Processing Professionals
Pre-screened and vetted.
Mid-level AI Backend Engineer specializing in LLM applications and scalable ML services
Mid-level Full-Stack Engineer specializing in AI-powered cloud applications
Mid-level AI Backend Engineer specializing in LLM applications and scalable ML services
Executive CTO/CPO and Product & Technology Leader specializing in Healthcare SaaS and AI/ML
Mid-level AI Backend Engineer specializing in LLM applications and scalable ML systems
Senior Software Engineer specializing in data platforms and FinTech/SaaS systems
JYOTHI N
Senior Data Scientist specializing in analytics, experimentation, and BI on AWS
“Data/ML practitioner focused on healthcare data quality and record linkage: analyzed 10M+ records, built anomaly detection and NLP-driven entity resolution, and automated AWS ETL/validation pipelines (Glue/Redshift/Lambda), cutting data errors by 40% and generating $500k in annual savings. Has hands-on experience with embeddings (Sentence Transformers/spaCy), FAISS vector search, and fine-tuning for domain-specific matching.”
Sean Membrido
Intern Software Engineer specializing in AI/ML and full-stack development
“Full-stack engineer with fintech and AI product experience: built HuddleAI end-to-end on Firebase/React, including a serverless LLM meeting-intelligence pipeline (FFmpeg + Google Speech-to-Text + GPT-4 with schema validation) and Slack notifications. At Gemini, owned a Postgres/Scala workflow change for wire deposit approvals that cut blocked registrations by 60% and emphasized correctness/compliance in UK/EU transaction-state UI.”
Intern software engineer specializing in AI, cloud, and full-stack systems
Junior Software Engineer specializing in distributed systems and edge AI
Mid-level Software Engineer specializing in full-stack and AI-driven systems
Mid-level Full-Stack Software Engineer specializing in cloud-native data platforms
Mid-level Mechanical Engineer specializing in medical robotics and machine learning
Senior Full-Stack Developer specializing in Python, AWS, and data/ETL systems
Principal Data Scientist specializing in LLMs, RAG, and enterprise AI products
Yu-Chun Lin
Intern Software Engineer specializing in C++/Python systems and automation
“Software engineer with experience delivering customer-facing solutions across consulting and engineering contexts (Deloitte, Coherent), including a finance reconciliation system and a firmware validation tool integrated into existing test infrastructure. Demonstrates strong on-site/customer collaboration, rapid iteration, and high-pressure debugging (CARLA demo fix), with measurable impact and a focus on adoption through familiar workflows and clear documentation.”
Swathi Sankaran
Senior Python Full-Stack Developer specializing in cloud, data engineering, and ML/GenAI
“Backend/data engineer with hands-on production experience building FastAPI services on AWS and implementing strong reliability/observability (CloudWatch, ELK, correlation IDs, alarms). Has delivered serverless + container solutions with IaC (CloudFormation/Terraform) and Jenkins CI/CD, and built AWS Glue/PySpark pipelines into S3/Redshift with schema-evolution and data-quality safeguards; demonstrated large-scale SQL tuning (45 min to 3 min on a 500M-row workload).”
jing wang
Mid-level Software Engineer specializing in enterprise AI for professional services
“Deloitte technical implementation lead who functioned like a pre-sales/solutions engineer for ABBYY's intelligent document processing within the Argus GenAI platform. They supported enterprise-scale rollouts across 10+ countries, tailored deployments for local market needs, and combined integration, compliance, and Python automation work to deliver 95%+ extraction accuracy.”
Javon Lee
Senior Software Engineer specializing in AI platforms and cloud-native systems
“Engineer with startup CTO experience and recent hands-on full-stack work at Microsoft and Clarity, focused on compliance and AML workflow platforms for financial services. Stands out for building scalable data and audit systems that reduced manual processing and improved performance, while operating effectively in ambiguous early-stage environments.”