Job Overview
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.

Minimum Qualifications

• Bachelor’s, Master’s, or PhD in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience.
• 3+ years of experience building and shipping machine learning systems.
• Strong proficiency in Python and experience with at least one major deep learning framework (e.g., PyTorch, TensorFlow).
• Solid understanding of modern deep learning concepts, training workflows, model
• evaluation, and experience working with real-world, production-oriented ML pipelines.
• Strong problem-solving skills and ability to work effectively in a fast-moving, collaborative environment.

Preferred Qualifications

• PhD in a relevant field with a research focus in robot learning, embodied AI, or visual perception.
• Experience with end-to-end ML systems, including data collection, training, inference, and deployment.
• Background in computer vision, perception, or multi-modal machine learning, including egocentric or human-centric perception.
• Familiarity with large-scale training, experimentation infrastructure, or production ML systems.
• Ability and interest in learning new problem domains, data modalities, and ML techniques quickly.
• Publications in leading venues, open-source contributions, or demonstrated impact in applied ML or AI systems.

Pay: From $160,000.00 per year

Benefits:

• 401(k)
• 401(k) matching
• Flexible schedule
• Health insurance
• Paid time off

Work Location: In person