Machine Learning Engineer - NOVA
REQUIRED: Robotics experience
Pre-Screening Questionnaire:
-Have you worked on a computer vision project
-Do you have exposure on Nova fine-tuning
Must Have Technical/Functional Skills:
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 robotics perception, VLMs, or multi-modal AI systems is highly desirable
Roles & Responsibilities:
Assist in fine-tuning NOVA and other vision-language models for robotic perception tasks
Curate and preprocess datasets from simulation and real-world environments
Evaluate model performance across tasks such as object detection, segmentation, and scene understanding
Collaborate with simulation engineers to validate models in Isaac Sim and Omniverse environments
Support real-world deployment and testing of tuned models on robotic platforms
Generic Managerial Skills, If any:
The engineer will play a critical role in bridging simulation and deployment pipelines for advanced perception systems.
Key Words to search in Resume:
ML Engineer, Computer Vision, NOVA Fine-Tuning, Vision-Language Models, Isaac Sim, Synthetic Data, Robotics AI, AWS ML Pipelines, Simulation Evaluation
Education:
Master’s/bachelor’s in computer science, AI, Robotics, or related field