We are looking for a Machine Learning Engineer to join our core team building scalable ML systems for real-world perception and embodied intelligence.

In this role, you will work on end-to-end machine learning systems, spanning data collection, model training, evaluation, and deployment. You will collaborate closely with researchers,

engineers, and product teams to turn complex real-world data into robust, production-ready ML solutions.

This role is well-suited for engineers who enjoy working across the ML stack, are comfortable operating in ambiguous problem spaces, and are excited about applying modern deep learning methods to real-world perception, human-centric, and embodied AI problems.

Responsibilities

• Design, build, and own end-to-end machine learning systems, from data exploration and model development to evaluation and deployment on large-scale, real-world data.

• Apply state-of-the-art ML techniques to new problem domains and optimize models and pipelines for performance, efficiency, and reliability in production environments.

• Drive measurable improvements in model performance, system robustness, and product capabilities through applied machine learning.

• Collaborate closely with cross-functional teams to translate research ideas and product requirements into scalable ML solutions.

• Contribute to technical design, code quality, and best practices, and help shape the long- term direction of the company’s machine learning platform.