Pre-screened and vetted.
Junior Software Engineer specializing in full-stack web and Android development
Intern AI/ML Engineer specializing in data science, NLP, and reinforcement learning
Mid-level Site Reliability Engineer specializing in Kubernetes observability and cloud infrastructure
Intern AI/Data Science Engineer specializing in LLM agents, data engineering, and predictive analytics
Mid-level Full-Stack Software Engineer specializing in FinTech and cloud-native systems
Junior Software Engineer specializing in LLMs, RAG, and Knowledge Graphs
Junior Full-Stack/Cloud Engineer specializing in AI and data-driven applications
Mid-level Machine Learning Engineer specializing in LLMs, multimodal AI, and backend systems
Intern Computer Vision/Perception Engineer specializing in LiDAR and autonomous systems
“Robotics/AV-focused engineer who built an end-to-end gesture controller for a GEM e2 autonomous vehicle using YOLOv8 pose and ROS, including model training, ROS perception nodes, and a safety-oriented state machine (stop override + hold-to-register). Also has internship experience at Intramotev integrating LiDAR object detection via Redis pub/sub and performing sensor-frame calibration (roll/pitch correction using ground-plane normals), plus Dockerized deployments and Gazebo-based testing.”
Mid-level Backend Software Engineer specializing in AWS cloud and FinTech platforms
“JP Morgan engineer and Texas A&M student web developer who has owned production systems end-to-end, including a real-time ML training workflow that improved internal search relevance by 30%. Experienced with AWS cloud migrations and operating containerized services on ECS with CloudWatch+ELK observability, Terraform infra, and Spinnaker CI/CD; also built event-driven pipelines with RabbitMQ and Elasticsearch at 1M+ record scale.”
Junior Full-Stack Software Engineer specializing in cloud-native microservices
“Backend engineer with hands-on IoT and AI product work: built a decoupled Raspberry Pi + AWS IoT Core weather monitoring backend and a Dockerized FastAPI LLM service on AWS ECS using OpenAI/HuggingFace with an emerging RAG layer. Also delivered measurable performance gains at DAZN by redesigning event-driven/serverless ingestion (SNS, S3->Lambda->DynamoDB), cutting latency ~30% and boosting throughput ~25% while automating ~90% of manual sync work.”
Intern Software Engineer specializing in LLM agents and full-stack development
“Embedded C++ engineer with Bosch automotive infotainment experience, owning real-time audio middleware modules with strict latency/memory constraints. Strong in profiling/optimizing deterministic behavior, debugging hardware-specific intermittent issues, and building automated test + CI pipelines; currently ramping up on ROS2 concepts (DDS, nodes/topics/services) to transition toward robotics.”
Junior Machine Learning Engineer specializing in AI, computer vision, and data systems
“Built and owned an end-to-end AV operations automation and dashboarding platform for USC event operations, used daily to coordinate hundreds of live events. Delivered a React/TypeScript full-stack system integrating Smartsheet APIs with strong reliability practices (typed contracts, validation/fallbacks, safe rollouts) and experience with queue-based microservice patterns (idempotency, retries, DLQs, monitoring).”
Mid-level Software Engineer specializing in distributed systems and AI-powered platforms
“Software engineer with experience spanning an SEL internship and Walmart, combining backend/data pipeline work (Python, Kafka, relational DBs) with DevOps practices (Docker, Grafana, GitHub/Jenkins CI/CD, GitOps). Notably contributed to a REST-to-GraphQL migration aimed at reducing cloud utilization and implemented testing strategies to validate the transition.”
Junior Full-Stack Developer specializing in React/Node and scalable web systems
“Built and owned Prism, a real-time collaborative coding platform, making key architectural choices around deterministic event ordering and a backend source-of-truth to improve trust under concurrent edits. Also created a Python-based bug analysis and test automation suite that became part of standard engineering workflow, cutting debugging time by ~95% while improving fault detection coverage.”
Intern Machine Learning Engineer specializing in NLP, RAG, and deepfake detection
“Early-career (fresher) candidate who built and deployed a production AI medical document chatbot using a RAG architecture (LangChain + Hugging Face LLM + Pinecone) with a Flask backend on AWS EC2 via Docker. Has experience troubleshooting real deployment constraints (model dependencies, disk space, container stability) and setting up continuous-style evaluation with fixed query test sets tracking relevance, latency, and error rate.”
Mid-level Full-Stack Developer specializing in cloud-native FinTech systems
“Built a lightweight internal JavaScript analytics tracker capturing user interactions (clicks, page views, custom events) with debounced batching, automatic session tracking, and offline event caching via a localStorage-backed append-only queue. Demonstrates practical performance optimization mindset (profiling, memoization/caching) and React performance tuning.”
Senior Full-Stack Developer specializing in scalable web platforms and automation
“Backend/full-stack engineer focused on TypeScript/Node.js systems, with hands-on ownership of a real-time telemetry and dashboard platform built on Kafka, Debezium, PostgreSQL, and GraphQL. Stands out for combining event-driven architecture, correctness/idempotency patterns, strong observability, multi-tenant security, and developer-friendly API design in production environments.”
Entry-level Software Engineer specializing in full-stack and FinTech systems
“Software engineer with AppFolio payments experience who shipped an end-to-end payment adoption rollout during a short internship, including full-stack implementation, stakeholder coordination, and real-time monitoring. Also built an insurance service AI agent inspired by his father's agency, combining structured document ingestion, RAG, and agentic integrations to improve reliability on dense policy documents.”