Simulation and Test Engineer

Overview Simulation and Test Engineer (Conversational AI) – Andromeda Robotics, South Melbourne, Victoria, Australia. Andromeda Robotics is an ambitious social robotics company with offices in Melbourne and San Francisco, dedicated to creating robots that seamlessly and intelligently interact with the human world. Our first robot, Abi, is a custom-built platform designed to be a helpful aid and intuitive partner in aged care homes. We are seeking a foundational member to build out our capabilities to train and test Abi in simulation, and to develop a robust testing infrastructure for our conversational AI systems and embodied character behaviours. Responsibilities Phase 1: Build the Test Foundation Define and stand up synthetic test environments for the AI/ML conversational stack Test areas: conversational AI (voice-to-voice chat quality, response appropriateness, tool calling accuracy) Memory system testing (context retention, recall accuracy, conversation coherence) Audio modelling and testing (multi-speaker scenarios, room acoustics, voice activity detection) Perception system testing (social awareness: face detection, gaze tracking, person tracking) Gesture appropriateness testing in collaboration with the Controls/ML team CI/CD and automated regression testing for all AI/ML subsystems Quality metrics custodian: elicit use cases, derive requirements, establish measurable quality metrics Requirements formalisation: gather, document, and trace requirements back to test cases Phase 2: Scale to ML Training Infrastructure Extend test environments into training data generation pipelines Investigate and stand up simulation tools (Unity, Unreal Engine, NVIDIA Isaac Sim) to support ML pipeline with synthetic data and validation Build infrastructure for fine-tuning character animation models on simulated multi-actor scenarios Enable ML-generated gesture development to augment hand-crafted animation workflows Create virtual environments with diverse social interaction scenarios for training and evaluation Develop a path to generate high-fidelity synthetic interaction data at scale Qualifications Bachelor or Masters in Computer Science, Robotics, Engineering, or a related field 5+ years of professional experience testing complex AI/ML systems (conversational AI, perception systems, or embodied AI) Strong programming proficiency in Python (essential); C++ experience is valuable Hands-on experience with LLM testing, voice AI systems, or chatbot evaluation frameworks Understanding of audio processing, speech recognition, and/or computer vision fundamentals Experience with testing frameworks and CI/CD tools (pytest, Jenkins, GitHub Actions, etc.) Familiarity with ML evaluation metrics and experimental design Proactive, first-principles thinker who is excited by owning a critical system at an early-stage startup Bonus Points Experience with simulation platforms (Unity, Unreal Engine, NVIDIA Isaac Sim, Gazebo) and physics engines Experience with character animation systems, motion capture data, or gesture generation Knowledge of reinforcement learning, imitation learning, or synthetic data generation for training ML models Experience with 3D modelling tools and game engine content creation Understanding of ROS2 for robotics integration Knowledge of sensor modelling techniques for cameras and audio Experience building and managing large-scale, cloud-based simulation infrastructure PhD in a relevant field Benefits The salary for this position may vary depending on factors such as job-related knowledge, skills, and experience. The total compensation package may also include additional benefits or components based on the specific role. Details will be provided if an employment offer is made. If you're excited about this role but don’t meet every requirement, apply anyway. Andromeda Robotics celebrates diversity and is committed to an inclusive environment for all employees. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. #J-18808-Ljbffr