Robotics Manipulation Engineer

CreateMe Technologies, Inc.•Newark, CA

4d•$135,000 - $160,000•Hybrid

About The Position

CreateMe is an AI robotics company pioneering automated manufacturing for soft materials, starting with apparel. Built on the belief that the Future of Fashion is Bonded™, the company has developed a unified platform that combines advanced robotics, proprietary adhesive bonding, and Physical AI to deliver a new standard of precision, consistency, and speed. By replacing stitch-based construction with digitally applied adhesives and automated material handling, the platform enables localized, on-demand production that reduces waste, shortens supply chains, and improves recyclability by design. Core technologies include Pixel™ micro adhesive bonding, the MeRA™ robotic assembly system, and Thermo(re)set™ reversible adhesive science, advancements that make scalable, automated production possible within compact, localized facilities. CreateMe partners with brands and manufacturers seeking to modernize how products are made. With more than 95 patents across robotics, adhesives, and Physical AI, the company is defining the infrastructure for bonded manufacturing globally. As a Robotics Manipulation R&D Engineer on the robotics team at CreateMe, you will bridge the gap between cutting-edge academic research and real-world manufacturing solutions. Your primary focus will be tackling one of the most exciting challenges in robotics: the manipulation of deformable objects. In this role, you will design, train, and deploy advanced robot policies to handle fabric manipulation tasks. You will serve as the technical nexus between research and production—developing prototypes, building infrastructure, integrating advanced sensors, and scaling algorithms to solve actual problems on the factory floor.

Requirements

Master’s or PhD degree in Robotics, Computer Science, Mechanical/Electrical Engineering, or a related technical field.
3+ years of hands-on experience in robotic manipulation, control systems, or applied embodied AI development.
Strong proficiency in Python and C++ within a production or advanced prototyping environment.
Proven experience deploying machine learning, reinforcement learning, or deep learning models onto real-world physical robots.
Proficiency with modern deep learning frameworks (PyTorch, JAX, TensorFlow) and robotics systems (ROS/ROS2, modern sim environments).
Solid understanding of kinematics, dynamics, motion planning, and systems-level robotic architecture.

Nice To Haves

Direct hands-on research or industry experience with deformable object manipulation (e.g., fabrics, textiles, cables, or soft matter).
Ph.D. in AI, Robotics, Machine Learning, or a related field with a focus on robotic manipulation.
Strong foundational understanding of statistics and linear algebra relevant to deep learning and robot state estimation (e.g., Kalman filters, Gaussian processes).
Familiarity with physics-aware simulation tools tailored for deformables.
Proven track record of applying robot learning techniques (Sim-to-Real, RL, Imitation Learning, Action-Conditioned World Models) to solve complex, tangible problems.
Publications at top-tier ML, computer vision, or robotics venues (e.g., CoRL, ICRA, RSS, NeurIPS, CVPR).
A product-oriented mindset with the ability to navigate tradeoffs between pure research exploration and scalable, reliable production deployment.

Responsibilities

Design, train, and deploy novel robotic manipulation policies (e.g., RL, imitation learning, diffusion policies) specifically tailored for handling fabrics and highly deformable textiles.
Architect and implement end-to-end manipulation pipelines that seamlessly integrate perception, state estimation, planning, and control for fabric manipulation.
Integrate multi-modal sensors (e.g., tactile sensors, advanced 3D vision, force-torque) to achieve robust state estimation and physics-aware reconstruction of deformable materials.
Build and leverage robotic simulation environments (including deformable physics simulations) at scale to train models and successfully transfer them to physical hardware.
Write, optimize, and maintain reliable, production-level Python and C++ code to deploy your models onto real-world robotic platforms.
Work closely with mechanical engineers, software teams, and product stakeholders to iteratively design custom end-effectors, tackle system bottlenecks, and translate operational needs into technical roadmaps.