About the job
Persona AI is at the forefront of developing and commercializing robust, multi-functional humanoid robots designed for real-world applications. With a founding team boasting decades of experience in humanoid robotics, bionics, and advanced product development, we have successfully delivered hardware that has reached the stars, plumbed the depths of the ocean, and entertained guests at Disney Parks. Our mission centers on producing aesthetically pleasing, reliable products at scale while cultivating an exceptional, customer-oriented team.
We are seeking a Machine Learning Engineer to lead our machine learning initiatives. Ideal candidates will have experience in bringing products to market, though we value aptitude and enthusiasm as well.
As one of the pioneering Machine Learning Engineers at Persona, you will have the unique chance to influence the design and development of our humanoid robots from the ground up.
Your Responsibilities:
Collaborate on the design and development of the Persona machine learning software stack, focusing on manipulation, navigation, locomotion, and perception.
Team up with the ML team to devise and implement a comprehensive strategy for developing machine learning models, ensuring alignment with cutting-edge research and development.
Engage with the team to design, test, and deploy software, machine learning pipelines, and data collection methodologies.
Monitor and assess the performance of models in real-world applications.
Foster collaborations with universities and industry partners.
Contribute to attracting, nurturing, and expanding our machine learning and autonomy teams.
Qualifications:
A strong sense of determination and resilience to tackle complex challenges in embodied AI.
Passion for teamwork in a fast-paced environment.
Over 3 years of experience in applying machine learning techniques to robotics.
Proficiency in deep learning frameworks such as PyTorch, JAX, or TensorFlow.
Experience with cloud computing platforms (AWS, Azure, GCP) for model development and data storage.
Deep understanding of current research in robot learning, including behavior cloning for manipulation and reinforcement learning for locomotion.