As a machine learning engineer, you will lead our customer-facing machine learning initiatives and the customization of our foundation models for challenging real-life robotics tasks. A crucial aspect of the role is to interface with our Simulation Engineering Team and Foundation Model Research Team to adapt our cutting-edge models and high-fidelity data pipelines to result in task-specific modules.
Machine Learning Engineering:
- Model Development: Implement and adapt machine learning models tailored for computer vision and robotics applications.
- Data Strategy: Formulate data collection and acquisition strategies for both synthetic and real-life data for model training.
- Performance Tuning: Continuously review and fine-tune models based on evolving data and customer feedback, and make use of effective MLOps practices.
- Technical Leadership: Collaborate closely with the engineering teams to uphold machine learning and software engineering best practices.
- Simulation Interface: Work with our team of simulation engineers to customize the simulation platform based on customer requirements for data generation or model evaluation.
- Foundation Model Collaboration: Interface with the Foundation Model Research Team to establish the base models that will be fine-tuned to meet customer specifications.
- Research: Keep abreast of the latest developments in machine learning and robotics to maintain our competitive edge.
- Bachelor’s degree or above in Computer Science, Robotics, or a related field. (Master’s preferred).
- A minimum of 5 years experience in machine learning, with a focus on robotics preferred.
- Pytorch, Python, OpenCV, Computer vision, Must Have
- In-depth understanding of machine learning algorithms, data structures, and performance tuning.
- Familiarity with programming languages such as Python, C++, or Java.
- Exceptional problem-solving abilities, with a knack for translating real-world problems into machine-learning tasks.
Excellent verbal and written communication skills.