Pre-screened and vetted.
Senior .NET Full-Stack Developer specializing in cloud-native microservices
Mid-level AI/ML Engineer specializing in financial risk, NLP, and MLOps
Senior Strategic Operations & Chief of Staff professional specializing in investor relations
Mid-level QA Automation Engineer specializing in healthcare test automation and DevOps
Senior Private Equity & Growth Equity Analyst specializing in M&A and fundraising
Senior Marketing Specialist specializing in integrated media and performance analytics
Senior QA Engineer specializing in automation, accessibility, and cross-platform testing
Mid-Level Full-Stack Java Developer specializing in Spring Boot, React, and AWS
Executive Engineering Leader (CTO/SVP) specializing in high-load platforms and GenAI/LLM systems
Senior Customer Success leader specializing in Enterprise SaaS and FinTech
Junior Software Engineer specializing in backend systems, QA automation, and AI/ML
Mid-level Financial Analyst specializing in FP&A, modeling, and investment analysis
Mid-level Full-Stack Engineer specializing in web platforms and financial systems
Mid-level Full-Stack Software Engineer specializing in React/Node and cloud-native web apps
“Full-stack engineer who built and iterated a CRM dashboard at ReplyQuick by sitting with end users, prioritizing blockers, and shipping frequent updates—improving usability and performance enough to replace a spreadsheet workflow within ~2 months. Demonstrates strong security fundamentals (OAuth2/JWT + RBAC) and practical microservices experience (decoupling a CRM API from a PDF-processing service via async processing and status tracking).”
Mid-level AI/ML Engineer specializing in NLP, computer vision, and recommender systems
“Built and deployed a production NLP sentiment analysis system at Piper Sandler to turn noisy, finance-specific customer feedback into scalable insights. Demonstrates strong end-to-end MLOps: fine-tuning BERT, improving label quality, monitoring for language drift, and automating retraining/deployment with Airflow and Docker (plus Kubeflow exposure).”
Senior Machine Learning Engineer specializing in LLMs, RAG, and Computer Vision
“Built a production LLM-powered clinical note summarization and retrieval system that structures patient/provider/payer discussions into standardized outputs (symptoms, treatments, clinical codes, and prior-auth decisions) and stores notes as embeddings for hybrid search and proactive prior-authorization prediction. Experienced with LangChain/LangGraph orchestration, RAG, and grounding against medical code databases, and has communicated model feasibility/limitations to business stakeholders (Virtusa/Comcast).”
Mid-Level Full-Stack Software Engineer specializing in Cloud, DevOps, and Platform Engineering
“Backend/Node.js-focused engineer who improved a widely used shared config/logging utility library by fixing a real-world async race condition (single disk read under concurrency) and adding stronger validation/testing, resulting in more deterministic services and faster startup/build/CI times. Also builds internal platform automation spanning Python/Go/TypeScript with strong documentation practices and security-conscious customer onboarding (e.g., sensitive Kubernetes clusters, HashiCorp Vault access issues).”
Mid-level Robotics/Mechatronics Engineer specializing in ROS 2, SLAM, and sim-to-real autonomy
“Robotics software engineer focused on sim-to-real deployment: built an Isaac Sim/Isaac Lab PPO training pipeline with domain randomization for vision-conditioned quadruped locomotion and integrated a RealSense D435i into a ROS2 stack on hardware. Also worked on an autonomous surface vessel, standardizing ROS2 interfaces across Jetson, microcontroller, GPS/IMU and motor controllers, using structured logging/replay to debug real-time oscillations and improve path tracking.”
Mid-level Data Scientist specializing in industrial IoT, predictive analytics, and generative AI
“ML/NLP engineer with Industrial IoT experience who built an end-to-end anomaly detection and GenAI explanation system: AWS (S3, PySpark, EC2/Lambda) pipelines feeding dashboards, plus transformer-embedding vector search to connect anomalies to noisy maintenance notes and past events. Demonstrated measurable impact (15% lift in defect detection; ~35% reduction in manual review; 35% fewer preprocessing errors) and strong productionization practices (orchestration, monitoring, rollback, data-quality controls).”
Mid-Level Software Engineer specializing in backend microservices and cloud-native systems
“Full-stack TypeScript engineer who has owned a real-time workflow/communication platform end-to-end in production (Node/TS + React, Postgres/Redis, Kafka, Docker/CI/CD). Demonstrates strong distributed-systems pragmatism—designing for failure with retries, DLQs, idempotency keys, and atomic writes—plus operational practices like structured logging, monitoring, and zero-downtime deployments.”