Pre-screened and vetted.
Junior Full-Stack Developer specializing in React, Node.js, and AI/LLM integrations
“Full-stack developer who owned and shipped an end-to-end web application for LeafNBeyond (React/Node/Postgres), deployed to production at leafnbeyond.com, with reported 35% sales growth and strong UX feedback. Also built Azure-based ETL pipelines using lakehouse/medallion architecture with validation and retry logic, and has AWS fundamentals from a master’s coursework (EC2, RDS, IAM, load balancing).”
Mid-level Full-Stack Python Developer specializing in AI/ML and backend APIs
“Python/Django backend engineer with open-source experience upgrading Archivematica to Django 4.2 LTS, including resolving a tricky breaking change in datetime parsing by implementing a preservation-safe legacy timestamp conversion layer. Also built a cost-efficient, reproducible Small Language Model (Microsoft Phi-3) fine-tuning pipeline that turns CSV product data into a domain-specific searchable Q&A chatbot, with emphasis on memory optimization and overfitting prevention.”
Junior AI/ML Engineer specializing in GenAI, RAG, and full-stack ML systems
“Built a university campus assistant chatbot (BabyJ/WWJ) using RAG and agentic routing with a FastAPI + React stack and JWT auth, focusing heavily on production concerns like latency and reliability. Uses techniques like speculative prefetching, smart intent routing, and rigorous eval/testing (golden sets, regression, edge cases) while collaborating closely with campus admin/advising teams to iterate based on real user feedback.”
Junior Data Scientist specializing in applied ML, LLMs, and analytics automation
“Research Analyst at Syracuse who deployed an LLM-powered lab automation system allowing researchers to run QCoDeS instrument workflows via natural language, with strong safety guardrails for real instruments and multi-instrument support. Also collaborated with non-technical stakeholders at iConsult on an audio classification/recommendation pipeline, translating business goals into metrics and Tableau dashboards with model comparisons and A/B test results.”
“LLM/RAG engineer at Connex AI who built and deployed a production healthcare agent to extract clinical insights from medical data/notes. Strong focus on real-world reliability—hallucination mitigation (citations, schema validation, confidence thresholds, rejection logic), custom LangChain orchestration (query rewriting, fallback paths), and production evaluation/observability—while collaborating closely with clinical SMEs to ensure clinical fit and time savings.”
Mid-Level Software Engineer specializing in Healthcare Data Platforms
“Backend/ML engineer with healthcare domain experience building secure Medicare/Medicaid data APIs and real-time patient risk scoring. Shipped an end-to-end ML pipeline (scikit-learn/XGBoost) served via SageMaker and integrated into Flask APIs, with strong production reliability practices (Kafka schema validation, regression replay, observability, drift monitoring, and human-in-the-loop guardrails).”
Junior Full-Stack Developer specializing in web development and AI research
“Early-career software engineer who has already owned a real-world web product end-to-end for a 100+ member university ACM organization, including requirements gathering, UI/UX improvements, hosting, CI/CD, and ongoing maintenance. Brings hands-on React and full-stack project experience with a strong bias toward practical execution, mobile-friendly design, and reliable delivery.”
Mid-Level Embedded Software Engineer specializing in real-time firmware and industrial automation
“Robotics software engineer focused on reliability in real-time sensor pipelines and ROS/ROS2 integration, with hands-on experience hardening systems against noisy data, dropouts, and network variability. Uses ROS introspection tools plus simulation (Gazebo/Webots) to diagnose latency and stability issues before hardware deployment, and supports repeatable rollouts via Docker and CI/CD.”
Mid-level Full-Stack Developer specializing in Python/Django and React
“Backend engineer at Hexanika who owned a real-time fraud-detection platform: built Django microservices, integrated a GenAI anomaly-scoring model, and optimized data/infra for low-latency production (including ~40% query-latency reduction). Experienced running containerized services on AWS/GCP with Kubernetes/GKE, GitHub Actions-based CI/CD + GitOps, and building Pub/Sub streaming pipelines and on-prem-to-cloud migrations.”
“Full-stack engineer with deep startup experience (pre-seed through IPO/SPAC) currently building a Next.js/TypeScript SaaS sports analytics platform with a complex Postgres-based entitlement/ACL system. Has delivered measurable UX/business impact (35% retention lift, 40% volume increase) and built production-grade daily ETL + model training/inference workflows with validation and checkpointing for reliability.”
Junior Data Analyst & Business Analyst specializing in BI, analytics, and process optimization
Mid-Level Full-Stack Software Engineer specializing in data pipelines, mobile apps, and AWS
Mid-level Data Scientist / AI Research Engineer specializing in LLMs, RAG, and applied ML
Mid-level Data Scientist specializing in computer vision and behavioral analytics
Mid-Level Application Support Engineer specializing in SAP, cloud IAM, and production operations
Mid-level Full-Stack/AI Engineer specializing in LLM microservices, RAG, and data pipelines
Mid-Level Software Engineer specializing in cloud platforms, search/LLM systems, and payments
Mid-Level Full-Stack Software Engineer specializing in web and mobile applications
Mid-Level Backend/API Engineer specializing in AWS and healthcare/first-responder systems
Mid-level Data Scientist specializing in GenAI, MLOps, and computer vision for robotics