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Vetted Reinforcement Learning Professionals
Pre-screened and vetted.
Mid-level Machine Learning Engineer specializing in MLOps, computer vision, and generative AI
Junior Robotics Software Engineer specializing in GNSS localization, perception, and controls
Senior Machine Learning Engineer specializing in MLOps and LLM/Agentic AI systems
Senior Software Engineer specializing in scalable platforms and AI-driven personalization
Junior Robotics & AI/ML Engineer specializing in autonomous systems and computer vision
Mid-level AI & Machine Learning Engineer specializing in production ML and LLM applications
Mid-level Software Engineer specializing in AI-driven systems and scalable backend services
Mid-level AI/ML Engineer specializing in LLMs, agentic systems, and MLOps
Mid-level Machine Learning Engineer specializing in optimization, RL, and graph neural networks
Mid-level AI/ML Engineer specializing in production ML, NLP, and computer vision
Mid-level AI Engineer specializing in LLMs, RAG chatbots, and cloud AI testing
Principal AI Platform Architect specializing in agentic AI and enterprise LLM infrastructure
Intern AI/ML Engineer specializing in generative AI and multimodal agentic systems
Mid-level Generative AI Engineer specializing in LLMs, NLP, and multimodal systems
Mid-level Software Engineer specializing in backend systems, distributed systems, and applied AI
Ishaan Kandamuri
Intern Aerospace/Robotics Engineer specializing in GNC, autonomy, and sensor fusion
“University robotics researcher graduating May 2026 who integrated an Intel RealSense D435i onto a TurtleBot3 (Jetson Nano) and built a ROS 2 node + OpenCV pipeline to feed color-based cues into navigation/path planning for RL grid-world experiments. Has hands-on ROS 2 experience spanning Gazebo simulation, Nav2, ros2_control, multi-robot namespacing, and ROS1-to-ROS2 bridging, plus CI/CD exposure (GitLab CI, Jenkins) from internships including aircraft navigation work.”
Karan Shah
Mid-level Software & Robotics Engineer specializing in autonomous systems and ROS 2
“Robotics software engineer focused on production-grade autonomy in GPS-denied environments, building full navigation stacks (perception, EKF/UKF sensor fusion, planning, control) in ROS2. Integrated YOLOv8/semantic segmentation/RL policies into real-time NAV2 pipelines via a custom perception-aware costmap layer, with emphasis on deterministic control loops, embedded GPU performance, and robust system observability/fault tolerance.”
kunj Golwala
Junior Robotics Perception Engineer specializing in autonomous navigation and robot learning
“Robotics software/perception engineer with production AMR experience at Symbotic, building a real-time SKU case re-identification pipeline used in high-volume Walmart/Target warehouse operations. Strong in ROS2 + Docker deployments on Jetson (TensorRT quantization) and system-level performance debugging, including cutting inference latency from ~13s to ~2s through architecture changes. Also has lab experience integrating SLAM/MPPI/behavior trees for rule-compliant navigation and distributed perception-to-UR5e manipulation systems (MoveIt/ros_control) with multi-camera sensing and 3D reconstruction.”
Rushi Reddy Lambu
Mid-level AI/ML Engineer specializing in Generative AI and MLOps
“GenAI/LLM engineer and architect who built and deployed a production generative AI financial forecasting and scenario analysis platform at McKinsey, leveraging Claude (Anthropic), LangChain, Airflow, MLflow, and AWS SageMaker. Demonstrates strong LLMOps/MLOps rigor (monitoring, drift detection, automated retraining) and deep experience implementing global privacy controls (GDPR, differential privacy, audit trails) while partnering closely with finance executives and legal/IT stakeholders.”