Machine Learning Engineer
- Assist in fine-tuning VLA (Vision-Language Alignment) models for robotic perception and interaction tasks
- Curate and preprocess multi-modal datasets (images, text, sensor data) from simulation and real-world sources
- Evaluate model performance for tasks such as semantic understanding, object recognition, and scene interpretation
- Collaborate with simulation engineers to validate models in Isaac Sim and Omniverse environments
- Support real-world deployment and testing of VLA models on robotic platforms
- Work with AWS teams to optimize training pipelines and model integration workflows
- Analyze model outputs and provide insights for iterative improvements
- Hands-on experience with PyTorch, TensorFlow, OpenCV, and vision-language models
- Familiarity with synthetic data generation, auto-annotation, and simulation tools (Isaac Sim, Omniverse)
- Experience with model evaluation metrics and performance tuning
- Knowledge of ROS/ROS2, Python, and C++ for robotics integration
- Exposure to cloud-based ML workflows (AWS SageMaker, EC2, S3) is a plus
- Prior work in multi-modal AI systems, VLMs, or robotics perception is highly desirable
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