Pre-screened and vetted in the Bay Area.
Mid-level AI Engineer specializing in agentic LLM systems
“Built and productionized a dual-agent LLM invoice-processing system for GFI Partners, adding guardrails and audit trails to earn stakeholder trust and drive adoption while cutting operational burden by 75%. Uses LangSmith observability to diagnose real-time workflow regressions and has experience teaching agentic AI concepts (e.g., at Carnegie Mellon) through hands-on, scaffolded demos.”
Intern Machine Learning/Robotics Engineer specializing in computer vision and 3D simulation
Intern software engineer specializing in backend, cloud, and security systems
Intern Perception/Robotics Engineer specializing in computer vision and embodied AI
Junior Forward Deployed Engineer specializing in AI solutions and production deployments
Senior Robotics Systems Engineer specializing in manipulation, motion planning, and real-time control
Intern Mechanical Engineer specializing in robotics, controls, and manufacturing
Mid-level Software Engineer specializing in data platforms and full-stack systems
Mid-level Software Development Engineer specializing in AWS incident management and AI analytics
Mid-level AI Engineer specializing in LLM agents, evaluation pipelines, and microservices
Intern Controls Software Engineer specializing in robotics and autonomous vehicles
Mid-level Software Engineer specializing in AI/ML and full-stack systems
Mid-level Control Systems Engineer specializing in automation, embedded systems, and hydrogen energy
Mid-level Machine Learning Engineer specializing in optimization, RL, and graph neural networks
Mid-level Software Engineer specializing in ML platforms and cloud-native backend systems
“Software engineer with experience at Google and the City and County of San Francisco building production AI systems, including a RAG-based internal support chatbot and ML-driven ticket priority tagging. Has scaled data/ML platforms with Airflow on GCP (1M+ records/day, 99.9% SLA) and deployed multi-component systems with Docker and Kubernetes (GKE), using modern LLM tooling (LangChain/CrewAI, Claude/OpenAI, Pinecone/ChromaDB, Bedrock/Ollama).”
Junior Robotics/Controls Engineer specializing in ROS2 autonomy, perception, and medical robotics
“Robotics software engineer/researcher at Stanford PDML Lab building VisualFT, a ROS2-based visual-tactile sensing system for compliant force-control guidance in acupressure/ultrasound-style manipulation. Also interned at Neocis (dental robotics) improving safety-critical collision detection using Bullet Physics with automated validation and CI (Jenkins/CDash).”
Intern Deep Learning Engineer specializing in LLM agents and on-device multimodal inference
Intern Software Engineer specializing in GenAI and backend systems
Senior Data Scientist specializing in ML search, recommendations, and generative AI
Intern AI/Software Engineer specializing in LLM agents and full-stack automation
Junior Software Engineer specializing in robotics and real-time distributed systems
“Robotics software engineer focused on low-compute navigation/SLAM: built a 6-DOF SLAM validation pipeline (IMU + 2D LiDAR + ultrasonic) producing ~1cm OctoMap accuracy and deployed it on an Intel Atom by optimizing particle-filter SLAM with a greedy max-likelihood update. Deep ROS 2 experience (executors, composable/lifecycle nodes, QoS, timestamping) plus simulation and deployment tooling (Gazebo C++ plugins, Docker, CI/CD, ROS 2 build farm) and drone navigation work with MAVROS/PX4.”
Junior Robotics Engineer specializing in motion planning and control
“Robotics software engineer who built a ROS2-based ping-pong ball interception system on a 7-DOF Sawyer arm, spanning real-time vision, trajectory prediction, and an MPC joint-velocity controller to hit a flying ball within ~1 second. Demonstrated strong real-time debugging and systems integration skills (timestamp-based latency analysis, event-based redesign, ROS2 QoS tuning) and is currently working with Isaac Sim in Docker with GitHub-based CI/CD for assembly-task simulation.”