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Vetted Neural Networks Professionals
Pre-screened and vetted.
Entry-Level Software Engineer specializing in full-stack JavaScript and machine learning
Mid-level Full-Stack Developer specializing in Java/Spring Boot, React, and AI/ML APIs
Junior Embedded Software Engineer specializing in interactive installations and real-time systems
Junior AI/ML Engineer specializing in LLMs, automation, and backend data pipelines
Entry-Level Software Engineer specializing in full-stack JavaScript and machine learning
Mid-level AI/ML Engineer specializing in fraud detection, credit risk, and NLP
Mid-level AI & Data Science professional specializing in MLOps, deep learning, and UAV research
Mid-level AI/ML Research Engineer specializing in NLP, LLM agents, and multimodal systems
Entry-Level Game Designer and Developer specializing in Unity and gameplay systems
Gene Ruan
Junior Computer Engineer specializing in machine learning and computer vision
“Software engineer with hands-on hardware/software crossover work: led an EMG circuit project using PSpice simulation and MATLAB-based data processing. Also contributed to an agriculture research computer-vision effort (hens/eggs tracking), building a PyTorch inference program and boosting model accuracy by ~10–20%, plus limited ROS 2 Humble exposure on an autonomous EV model with LiDAR/camera detection.”
Abdirazak Farah
Entry-Level Full-Stack/IoT Engineer specializing in AI-powered applications
“New-grad software engineer who built a real-world smart-city traffic camera/operations dashboard pitched to Peachtree Corners, GA, integrating Bosch cameras with an MQTT/Node-RED/InfluxDB pipeline and Grafana visualizations. Implemented rule-based alerts (including SMS dispatch for janitorial cleaning) and improved production reliability with queuing, redundancy, monitoring, and load testing, reaching ~99% message delivery. Actively seeking onsite, customer-facing roles with travel.”
Priyanka Palnati
Entry-Level Computer Science Graduate specializing in ML, data analytics, and cybersecurity
“Built a Smart Resume Screening tool with a React frontend and a Python backend, owning most backend architecture and delivery. Implemented FastAPI endpoints for file upload and NLP/ML inference, created the end-to-end resume classification pipeline, logged predictions to a database for accuracy tracking, and deployed a Dockerized service optimized for low-latency, concurrent processing.”
Junior Software Engineer specializing in full-stack development and machine learning
Junior Full-Stack Software Developer specializing in cloud-native apps and data/AI
Junior Machine Learning Engineer specializing in LLMs, RAG, and fine-tuning
Mid-level Research Assistant specializing in interpretable ML and AI evaluation
Junior Game QA Tester and Gaming Content Creator specializing in gameplay analysis
“Built and shipped a production-grade RAG-powered news summarization and Q&A product, tackling real-world issues like retrieval drift, hallucinations, latency, and autoscaling deployment (Docker + FastAPI + Streamlit Cloud). Experienced in end-to-end ML/LLM workflow automation using Airflow, Kubeflow Pipelines, and MLflow, and has demonstrated business impact (40% inference precision improvement) through close collaboration with non-technical stakeholders at Evoastra Ventures.”