DeepMind carries out and publishes research into the intersection between machine learning and robotics. We’re looking for mechanical engineers who can work closely with our researchers to optimise robotics systems for learning based methods.
We are looking for a full time mechanical design engineer with proven experience in CAD, structural analysis and testing. The successful candidate will have a key role in optimising and upgrading existing robots and providing general mechanical engineering support.
The ideal candidate should possess a Mechanical Engineer degree and be deeply interested in the research activities at Deepmind. In particular, they should be interested in applying machine learning to parametric design. The candidate should be able to demonstrate:
Design and optimise 3D/2D models of robot parts and assemblies.
Interact with external contractors (e.g. workshops, system integrators, manufacturers and suppliers) to evaluate nonstandard parts.
Experience with practical 3D printing.
Generate detailed technical documentation for 3D/2D assembly and parts manufacturing.
Troubleshoot mechanical issues.
Collaborate with other engineering disciplines (electronics, software) to ensure the successful integration of their designs with the rest of the system.
Proficiency in hardware design and mechanism analysis with a proven portfolio of practical designs and excellent hands-on practical skills.
Excellent knowledge of design software tools (primarily with Pro Engineer, ANSYS, other relevant also welcome) is a must.
Experience with parametric design and experience in scripting the extraction of dynamic parameters from CAD project files (e.g. bar and foo).
Strong expertise in mechanical design, preferably with experience in the field of robotics
Experience in developing test fixtures, conducting tests, and iteratively improving designs
Demonstrated understanding of metrology and GD&T
Fundamental understanding of stress mechanics
At least two years of work experience
Excellent working knowledge of at least one industry standard CAD package, including both drafting and modelling packages
Team player with good oral and written communication skills (English language)
Willingness to integrate into a multidisciplinary, dynamic, international research group
Experience with finite element analysis, specifically analysing bolted connections and stiffness optimisation.
Understanding of strain gauging techniques and sensor selection.
Experience with automation in an industrial setting.
Knowledge of Python and/or C++.
Experience with advanced AM technologies and workflow (e.g. SLS).
With passion, ambition and a lifelong commitment to learning, our close-knit team support, challenge and inspire each other to be the best they can be every day. The culture we’ve created is as exceptional as our people. Our unique approach combines the best from academia and business to enable and encourage deep collaboration across all groups leading to fast and creative progress. This drives and accelerates our ambitious research program, yielding innovative breakthroughs at the forefront of AI research and application.
We are always looking for outstanding individuals from diverse backgrounds, who want to be part of this phenomenal team. We offer an inspiring and collaborative environment and the opportunity to learn from the best in field, whilst working on ground-breaking technology with extraordinary impact.
Caractéristiques de l'emploi
|Catégorie emploi||Informatique, Ingénieur mécanique, Machine Learning|
|Qualification||Ingénieur mécanique, Connaissance de Python et / ou C ++|