Pre-screened and vetted.
Junior Software Engineer specializing in full-stack web development and test automation
“Full-stack engineer who built and owned a production workflow/kanban-style drag-and-drop system in Next.js (App Router) with Postgres/Prisma, including reusable component abstractions, Cypress E2E coverage, and post-launch performance/bug ownership. Notable for measurable impact (25% faster UI dev, ~30% query perf improvement) and for leading an incremental Express→NestJS migration that reduced technical debt (~40%) through better structure, docs, and team enablement.”
Senior Game & XR Developer specializing in immersive VR/AR/MR experiences
“Unity game developer who built a Twitch chat integration enabling a streamer's audience to actively participate in gameplay, boosting engagement and virality. Has hands-on multiplayer experience with Photon, including RPCs/synced variables and designing for disconnects, late-joins, and low-bandwidth data transfer, and uses Cursor/AI agent workflows to accelerate feature development while maintaining code quality.”
“Software/product engineer who has owned a consumer iOS dating app from customer discovery through roadmap execution, while also shipping an in-app LLM-powered support/feedback bot. Brings a mix of product sense and backend systems experience, including rebuilding a race-condition-prone event orchestration system and designing microservices to handle arbitrary black-box production data.”
Mid-level Software Engineer specializing in integrations and automation
“Union College robotics graduate with hands-on ROS experience building an independent “waiter bot” that took spoken orders (Mozilla DeepSpeech), used OpenCV, and navigated via SLAM on a TurtleBot with LiDAR. Also led the Union College Robotics crew for four years and implemented PID control for micromouse maze robots; has additional software deployment experience with Dockerized FastAPI and CI/CD from coursework.”
Senior Full-Stack AI/ML Engineer specializing in MLOps and GenAI
“Senior backend/data engineer who has built and maintained HIPAA-compliant, real-time clinical FastAPI services on AWS, orchestrating ML/LLM and vector DB calls with strong reliability patterns (auth, timeouts/retries, graceful degradation, idempotency). Also delivered AWS IaC/CI-CD (Terraform/Helm/GitHub Actions) across EKS/Lambda/SageMaker and built Glue/Spark ETL with schema evolution and data quality controls, plus demonstrated large SQL performance wins (15 min to <9 sec) and hands-on incident ownership.”
Junior Backend Engineer specializing in cloud APIs and AI-enabled systems
“Built and shipped "OnCall Copilot," a production Slack-based RAG assistant that answers on-call questions from runbooks and postmortems with citations using a FAISS vector index. Emphasizes reliability and measurable performance via strict guardrails ("no evidence, no answer"), evaluation metrics, drift monitoring, and operational hardening with Docker, logging, health checks, and offline fallback.”
Mid-level Backend Software Engineer specializing in Java/Spring Boot and AWS microservices
“Owned and stabilized Decathlon e-commerce payment services, taking a prototype reliability effort to production by implementing failure detection/retries, load testing, and DB performance optimizations—reducing payment failures and cart abandonment. Also demonstrates an LLM/agentic workflow support mindset with strong observability, rapid incident diagnosis, and durable prevention via RCA, safeguards, and regression/replay testing, plus experience supporting sales/support with technical reassurance.”
Junior Solutions Engineer specializing in full-stack automation and LLM prompt engineering
“Built and productionized an LLM-powered customer support system using a RAG architecture with structured document ingestion, embedding retrieval, and prompt templates for product-specific grounding. Experienced diagnosing live agent/workflow failures (e.g., retrieval regressions after new docs) by refactoring ingestion/chunking and adding grounding constraints plus evaluation benchmarks. Also supports go-to-market by joining discovery calls, shaping MVP workflows into demos/prototypes, and creating post-launch documentation to drive adoption.”
“Software engineer with experience spanning healthcare middleware (patient records + insurance integration) and an AI fantasy football product built with React/TypeScript, Firebase, API gateways, and pandas-based data pipelines. Has hands-on microservices scaling experience (latency mitigation, async migration, state-based redesign) and built an internal feature-toggle dashboard that improved demo efficiency and sales outcomes.”
Mid-level Software Development Engineer specializing in Python, APIs, and AWS
“Backend engineer with experience modernizing legacy systems and building modular Python/Flask services, including a REST-to-GraphQL migration for an e-commerce platform that improved API response time by 45%. Strong in performance and scalability work across PostgreSQL/SQLAlchemy (indexing, JSONB, N+1 fixes, connection pooling) and high-throughput systems (Celery + Redis), plus integrating ML microservices with TorchServe, Kafka streaming, feature stores, and Prometheus/Grafana monitoring.”
Mid-level Machine Learning & Generative AI Engineer specializing in AI agents and LLM workflows
“Customer-facing AppSec/solutions engineer with experience securing cloud-native AI/LLM deployments on Azure and Kubernetes. Led threat modeling and production hardening (Key Vault secrets migration, least-privilege IAM, rate limiting, structured logging/monitoring, LLM guardrails) and has supported retail search/catalog platforms using Elasticsearch, including performance triage and rollout playbooks that improved customer trust and enabled engagement expansion.”
Junior Software Engineer specializing in full-stack tools and LLM inference infrastructure
“Full-stack/edge-focused engineer who took a manual, terminal-based AI calibration workflow and turned it into a web-enabled remote calibration system designed for low-bandwidth 5G field deployments, now used across 85+ field sites. Experienced operating edge fleets with versioned rollouts, Kubernetes-based cloud monitoring, and Prometheus/Grafana observability, plus refactoring fast-moving AI codebases for modularity and strong typing.”
Junior Robotics Engineer specializing in ROS 2, SLAM, and simulation
“Robotics software engineer with ~3.5 years in ROS/ROS2 mobile robotics, SLAM, and control who owned end-to-end integration for a sim-to-real mobile platform (Zephyr), including ros2_control, EKF sensor fusion (IMU + Vicon), and Gazebo validation with quantified accuracy. Also built a multi-drone CSLAM stack integrating ORB-SLAM3 and PX4 offboard control, scaling via namespaces, synchronization/QoS discipline, and performance debugging with ros2_tracing.”
Intern Robotics & AI Researcher specializing in autonomous navigation and sensor fusion
“Robotics software engineer who built a ROS 2 Humble autonomous hospital-equipment detection/localization robot end-to-end in Gazebo (custom worlds/models, Nav2 waypoint navigation, YOLOv8n perception, TF2-based depth fusion) and solved real-time integration issues via multithreading and QoS tuning. Also implemented and tuned an MPPI controller to enable smooth reverse parking on an OpenPodCarV2 platform, including real-world reverse engineering and hardware/software debugging.”
Mid-level AI & Computer Vision Engineer specializing in edge robotics perception
“Master’s thesis engineer who built and deployed a continuous real-time perception + state estimation + control loop under tight latency constraints, owning both software architecture and hardware integration. Strong ROS 2 fundamentals with a systems-first approach—stabilizes robotic behavior by instrumenting, logging/replaying real data, and fixing timing/synchronization issues rather than treating failures as purely algorithmic.”
Junior Robotics & ML Engineer specializing in simulation, control, and perception
“Robotics engineer focused on simulation, modeling, and control, with hands-on sim-to-real experience from a soft, foldable “grasshopper” robot where friction/contact physics and servo dynamics drove real-world performance gaps. Built a ROS 2 voice-operated TurtleBot system integrating YOLOv5 + stereo depth for object picking with an attached arm, and debugged AMCL/SLAM to cut localization error from 10–13 cm to ~5 cm. Currently developing a quadruped in MuJoCo with a 3-layer control stack (RL + MPC + PD) and an RL training pipeline in JAX ahead of hardware.”
Junior Machine Learning Engineer specializing in Document AI and LLM-powered workflows
“Built and owned a customer-facing Document Intelligence Service for legal contract analytics at Noasis Digital, delivering extraction/summarization with careful accuracy controls (confidence thresholds, versioned deployments, production logging). Also developed a React/TypeScript document review app and internal QA dashboard, and has hands-on microservices experience with async messaging (RabbitMQ), timeout tuning, and centralized structured logging for reliability at scale.”
Mid-level AI Engineer specializing in Generative AI, LLM fine-tuning, and RAG systems
“Built and deployed production LLM applications including a natural-language-to-read-only-SQL system focused on ambiguity handling and query safety (schema whitelisting, intent validation, confidence checks, deterministic execution). Experienced with LangChain-based, modular agent orchestration and RAG document QA for large PDFs, with a metrics-driven testing/evaluation approach and cross-functional delivery with marketing on an AI content recommendation/search tool.”
Intern AI/ML Software Engineer specializing in LLMs, NLP, and multimodal systems
“Built and deployed a production AI-powered personalized learning platform (Django + FastAPI) featuring an LLM+RAG tutoring assistant and automated grading. Demonstrates strong applied LLM reliability engineering (structured JSON outputs with Pydantic validation, hallucination control via FAISS-based RAG thresholds and refusals) plus scalable async microservice design and Airflow-orchestrated ETL across AWS/GCP.”
Junior Full-Stack Software Engineer specializing in cloud-based web applications
“Product-focused full-stack engineer with strong performance and reliability instincts: improved production page responsiveness by 15% via lazy loading and render optimization, and built a polished React+TypeScript filtering dashboard with URL-synced state for shareable views. Also designed and operated a Django REST backend with versioning, token auth, structured logging, and API tests, and has handled real production scaling issues through PostgreSQL query-plan analysis and indexing.”
Senior Data Scientist & Machine Learning Engineer specializing in computer vision and production ML
“PhD in computer engineering who has built production-oriented ML/NLP systems for space-weather prediction using Spark-based ETL on noisy satellite sensor logs. Strong in entity resolution and semantic search—fine-tuned E5 embeddings with contrastive learning and deployed to Pinecone, improving top-5 retrieval precision by 25%—and emphasizes scalable, observable pipelines with Airflow, Docker, and CI/CD.”
Junior Autonomous Driving Perception Engineer specializing in sensor fusion and SLAM
“Robotics software engineer with thesis work optimizing the Autoware perception pipeline via DDS/synchronization tuning for lower latency and better throughput, plus hands-on ROS1/ROS2 experience deploying perception (YOLOv8) and SLAM/localization on real vehicles and delivery robots. Has practical debugging depth (Kalman filter crashes, transformation/scan-matching issues) and CI/CD automation experience with Jenkins.”
Junior AI Engineer specializing in LLM systems, RAG, and scalable cloud AI
“Built and shipped production LLM agents for real-time, high-concurrency conversational systems, including a RAG-based pipeline with dynamic multi-provider routing and failover that achieved 99.99% reliability and sub-800ms latency. Also architected a UAV telemetry chatbot with tool-calling (anomaly detection/summarization), strict schema validation, and robust eval/monitoring loops, cutting tool-call errors by 30% and reducing operational costs by 90%.”
Mid-level XR Software Engineer specializing in real-time AR/VR digital twins
“Built and owned an end-to-end real-time IoT telemetry backend that powers a digital twin experience on a Meta Quest headset, integrating Cisco LoRaWAN sensors and external REST data sources. Migrated from Azure Functions to a FastAPI service to overcome firewall constraints, add caching/fallback reliability, and significantly reduce operating cost while improving performance and evolvability.”