Are you excited about AI Engineering ?
Do you want to be a part of AI research team?
If yes, We have an excellent opportunity as we are hiring for AI Engineer based out of Redmond, WA (Hybrid). If interested in applying please send your updated resume to uppender.
Any references are highly appreciated.
This is a fulltime opportunity
Top Skills Required
1. Experience with Linux
2. Experience with Python
3. Experience with Configuration management.
In addition : 2+ ROS / ROS2
2+ ROS / ROS2
2+ TensorFlow
2+ Any sort of machine learning packages.
- Purpose of the Team : The purpose of this team is AI research team. Teach robots to do new skills. Software and hardware engineers integrate.
- Key projects : This role will contribute to supporting the researchers so they can do their job.
The primary consideration for this position is a preference for candidates with experience in robotics or reinforcement learning, rather than those specializing in natural language models or computer vision.
Our team seeks a Machine Learning Engineer to advance the development and improvement of our software foundation and tools vital for training state-of-the-art AI models.
Your role will be centered on creating strong, scalable, and efficient training infrastructures and frameworks facilitating the full spectrum of the machine learning process, from handling data to deploying models.
In collaboration with researchers and software engineers, you'll ensure that training systems are smoothly integrated and functioning, expanding the limits of AI's capabilities, especially in practical robotics scenarios.
Additionally, you will investigate innovative methods to effectively utilize diverse datasets within our training framework.
Responsibilities
- Create and uphold efficient, scalable, and distributed training systems including data preprocessing, training orchestration, and model assessment for training large-scale AI models.
- Enhance the efficiency of training procedures to improve performance and use of resources, while maintaining scalability and dependability.
- Collaborate with researchers to create training and evaluation pipelines for state-of-the-art algorithms.
- Develop and design benchmarks for evaluating ML models.
- Perform training and and fine-tuning of foundation models for robotic applications .
- Monitor and analyze pipelines, identifying bottlenecks and proposing solutions to improve efficiency and performance.
- Ensure the robustness and reliability of the training infrastructure, including automated testing and continuous integration.
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