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Simulation Engineer
1 month ago
Welcome to Silana
At silana, we're rewriting the rules of fashion with cutting-edge robotics. As pioneers in sustainable manufacturing, we've developed groundbreaking technology that automates the entire garment production process – from fabric to finished product.
We are a VC-backed startup with offices in Europe and the US.
As our Simulation Engineer, you will play a pivotal role in defining and refining our simulation methodologies, fostering the creation of digital twins.
About You:
You enjoy working on early-stage teams and have experience designing, prototyping, and validating mechanical systems. You thrive in uncertain environments and look forward to finding solutions for high-reaching projects.
As part of the engineering team, you will design the mechanical subsystems for our robotic cell within our revolutionary new manufacturing process.
Key Responsibilities:
- Own the simulation foundation for developing the world’s first sewing robot.
- Define our approach to modeling the robot and the world in simulation.
- Develop and oversee the tooling that enables the creation and testing of full digital twins.
Minimum Qualifications:
- Bachelor's degree in computer science or a related technical field.
- At least 4 years of experience working within engineering teams.
- Demonstrated experience with simulation frameworks and applying simulations to expedite real robot development.
- Comprehensive skill set ranging from GPU utilization to 3D asset modeling.
- Proficiency in Python or C++, with a readiness to learn new languages or technologies.
- Ability to work across different platforms such as Git, Docker, networking, Linux.
- Solid foundation in mathematics, encompassing 3D geometry, linear algebra, physics, dynamics, and numerical modeling.
- Enjoys working in a fast paced, collaborative and dynamic start-up environment as part of a small team.
- Pragmatic and customer-focused approach.
Preferred Qualifications:
- Advanced degree (master's or PhD) in Computer Science, Computer Engineering, or Electrical Engineering.
- Expertise in dynamic physical system modeling and simulation, including contact, collision, controls, dynamics, sensor and actuator modeling.
- Experience with large-scale parallel simulations for deep learning model training.
- Familiarity with Isaac and/or Ignition/Gazebo simulation environments.
- Knowledge of sim-to-real comparisons, fidelity assessments, and validation techniques.
- Proficiency with ROS2 and low-level physics APIs.
- Background in engineering management, machine learning, design, and architecture.
- Proven experience in robotic or autonomous vehicle simulation projects.
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