Machine Learning Engineer (Human pose)

An early-stage AI and robotics startup is looking for a Machine Learning Engineer to help build production-grade machine learning systems for perception and embodied intelligence applications.

The role spans the full machine learning lifecycle, including data collection, model development, evaluation, optimization, and deployment. You will work closely with research and engineering teams to transform complex real-world data into scalable, reliable ML solutions for intelligent systems.

This opportunity is ideal for engineers who enjoy working across the entire ML stack, thrive in fast-moving environments, and are interested in applying modern deep learning techniques to perception, computer vision, multimodal learning, and robotics-related challenges.

Key Responsibilities

• Build and maintain end-to-end machine learning pipelines from data preparation through model deployment.
• Develop and optimize deep learning models for real-world perception tasks with a focus on performance, scalability, and reliability.
• Improve model quality and production systems through experimentation, evaluation, and iterative development.
• Partner with research, engineering, and product teams to translate ideas into production-ready machine learning solutions.
• Contribute to engineering best practices, system architecture, and the long-term direction of the company's ML platform.

Required Experience

• Degree in Computer Science, Machine Learning, Engineering, or a related technical discipline, or equivalent industry experience.
• Several years of experience developing and deploying production machine learning systems.
• Strong Python programming skills and experience with modern deep learning frameworks such as PyTorch or TensorFlow.
• Solid understanding of deep learning, model training, evaluation methodologies, and production ML workflows.
• Strong analytical and problem-solving abilities with experience working in collaborative, fast-paced teams.

Preferred Experience

• Advanced degree with research experience in areas such as computer vision, robotics, embodied AI, or machine learning.
• Experience building complete ML systems covering data pipelines, model training, inference, and deployment.
• Background in perception, multimodal learning, or vision-based machine learning.
• Experience with large-scale training infrastructure, experimentation platforms, or production ML environments.
• Ability to quickly learn new domains, datasets, and machine learning techniques.
• Research publications, open-source contributions, or other evidence of technical impact are beneficial.

What You'll Find

• Opportunity to work on technically challenging problems at the intersection of AI, perception, and robotics.
• Collaborative engineering culture with significant ownership and autonomy.
• Competitive compensation, meaningful equity, and strong career growth opportunities.
• Close collaboration with experienced engineers and researchers working on next-generation intelligent systems.