Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in computer vision and generative AI
Mid-level AI & Data Engineer specializing in cloud ML, RAG systems, and ETL automation
Mid-level AI/ML Engineer specializing in generative AI, NLP, and MLOps
Mid-level Data Scientist specializing in deep learning, NLP, and time-series forecasting
Mid-level Generative AI/ML Engineer specializing in LLMs, RAG, and MLOps
Mid-level Data Analyst specializing in BI, analytics, and data engineering
Mid-level MLOps/Machine Learning Engineer specializing in cloud-native production ML
Intern AI/ML Engineer specializing in NLP, graph analytics, and agentic RAG systems
Mid-Level Software Engineer specializing in ML and Generative AI applications
Mid-level AI/ML Engineer specializing in risk modeling, healthcare analytics, and MLOps
Senior Data Engineer specializing in Machine Learning and Healthcare Data Platforms
Junior Software Engineer specializing in full-stack web development and machine learning
Entry-Level AI Engineer specializing in NLP and LLM-powered applications
“AI engineer who built an agentic, production-deployed LLM workflow for tobacco violation parsing and automated multi-case creation, using six specialized agents and a human-in-the-loop confidence-threshold routing design. Addressed data privacy constraints by generating synthetic datasets with LLM prompting, and orchestrated reproducible end-to-end pipelines in LangChain with robust testing and evaluation (precision/recall, micro-F1).”
Mid-level Data Engineer specializing in ETL pipelines on GCP
“Full-stack engineer from Larix Technologies who led a Next.js migration feature: an internal real-time workflow status dashboard built with App Router/TypeScript using server components for initial render and client polling for live updates. Demonstrates strong post-launch ownership—monitoring latency/error rates, adding caching and payload reductions, and optimizing Postgres queries/indexes—plus experience building durable RabbitMQ-based message routing workflows with idempotency, retries, and dead-letter queues.”
Junior Robotics Engineer specializing in industrial automation and 3D perception
“Robotics software engineer at Quant Robotics focused on perception for automated welding/assembly cells, working with LMI Co-Cutter 3D sensors and point-cloud registration. Previously implemented ROS 2 Humble navigation on a Clearpath Jackal by rewriting the NAV2 local controller with a constrained NMPC approach, optimizing for low-latency behavior via C++ and GPU offload. Hands-on with industrial ABB robots (IRB 6700/2600), multi-frame calibration, simulation in Gazebo/RViz, and Docker-based deployment/testing workflows.”
Junior Software Engineer specializing in Odoo, web performance, and backend systems
“Full-stack developer who shipped LLM-powered customer support automation, including an AI call center designed for always-on, high-concurrency real-time phone handling. Also built a WhatsApp lead-conversion chatbot using Zapier webhooks, Redis state, and Twilio messaging, and reports measurable outcomes (+11% customer satisfaction, ~7% cost reduction) while using GPT-4.1.”
Junior Machine Learning & Full-Stack Engineer specializing in applied AI systems
“Master’s thesis focused on building and deploying a gait-based biometric authentication system using mobile accelerometer time-series data as an alternative to passwords/2FA. Emphasized real-world robustness by addressing sensor noise and variability (phone placement, walking speed, footwear) and improving safety using biometric metrics like FAR/FRR and EER, while collaborating closely with a non-ML thesis advisor.”
Junior Software Engineer specializing in backend and cloud systems
“Full-stack engineer with hands-on experience spanning analytics products and fintech infrastructure. Built a YouTube Data Aggregator end-to-end in 2025 with ingestion, dashboards, and predictive modeling, and also shipped Stripe webhook/payment systems at FinPay supporting $5M+ in transactions with 99.9% uptime.”
Intern Data Scientist specializing in LLM agents, RAG, and real-time ML pipelines