About RecogniRecogni’s mission is to design a vision-oriented artificial intelligence system from the ground up. The system will deliver unprecedented inference performance through novel edge processing, allowing vehicles to see farther and make driving decisions faster than humans while consuming minimal amounts of energy.Backed by GreatPoint Ventures, Toyota AI Ventures, BMW i Ventures and other leading VC partners, the company is headquartered in San Jose, California with additional operations in Munich, Germany.About the role
Our technology thrives through the synergistic interplay of different disciplines involved in the realization of our product: hardware, silicon, embedded software, sensors, AI, computer vision. Most of the innovations represented in the more physical sides of our approach would not be effective without their AI-counterparts integrated into our training pipeline. Custom number systems, our proprietary compression schemes, sensor-related schemes, sensor aging and dirt modeling - there is a long list of hardware- and real-world-specific aspects that need to be represented within the actual training of our neural network stack. Your job will be to make sure that our neural networks are trained under circumstances that are identical to the ones that our module is exposed to in the actual AV - down to the last bit.
- Conceptualize, develop and release AI functionalities around compression, quantization, multi-loss, knowledge distillation, massively parallel training and every other technique that is part of bringing our synergistic system-level approach to market
- Release your work aligned with our in-house libraries as well as in compliance with automotive safety standards
- Coordinate with other departments (hardware, embedded software, sensors, product)
- Pro-actively maintain up-to-date knowledge of our field through papers, blogs, conferences, meetups
- Master or higher degree in Electrical Engineering, Robotics, Computer Science or AI
- 2+ years of successful experience in developing novel AI approaches with a focus on realtime applications
- Ability to quickly extract relevant information from publications in our field
- Very familiar with/fluent in the latest versions of the following tech stack (ordered by relevance):
- TensorFlow, Python, Git(Hub/Lab)
- CUDA, C++
- GCP, Google TPU, Nvidia (TensorRT)
- Solid knowledge in the fields of:
- Loss function and regularizer design, quantization, multi-task learning, knowledge distillation
- CNN/DNN hardware acceleration
- In-depth understanding of the implication of architectural model design decisions (e.g. ResNet pre/post activation, single- vs. two-stage, U-Net vs. DeepLab, ...)
- Object Detection, Segmentation, Depth Estimation
- Chip / System-level AV integration architecture, RTL/Verilog
Why you might want to join the Recogni team
- Ground floor opportunity with the team; be part of shaping one of the most exciting new companies.
- Learning and development opportunities from a highly diverse and talented peer group, including experts in a wide range of fields, from Artificial Intelligence & Computer Vision to Systems & Device Engineering to Support & Operations
- Beautiful modern work space.
- Perks including meals, snacks, drinks, gym, conference attendances and us!
- Sharp, motivated co-workers in a fun office environment
- Employee Stock Purchase Plan
Recogni's culture was built on the following values that are equally important to us as business:
- Put people first. We only succeed when our people succeed.
- Ethics and integrity always; Being open, honest, and respectful of everyone.
- Think Big. Be ambitious and have audacious goals.
- Aim for excellence. Quality and excellence count in everything we do.
- Own it and get it done. Results matter!
- Make Each Person Better together than they would be as an individual.
- Embrace each others’ differences.
- Embrace that there will be differences.
Recogni is an equal opportunity employer. We believe that a diverse team is better at tackling complex problems and coming up with innovative solutions. All qualified applicants will receive consideration for employment without regard to age, color, gender identity or expression, marital status, national origin, disability, protected veteran status, race, religion, pregnancy, sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.