Deep Learning Engineer, Autonomy
Palo Alto, CA
At Lyft, our mission is to improve people’s lives with the world’s best transportation. To do this, we start with our own community by creating an open, inclusive, and diverse organization.
We care deeply about delivering the best transportation experience; this means the best experience for the passenger and the best experience for the driver. We believe this quality of service can only be achieved with a deep understanding of our world, our cities, our streets… how they evolve, how they breathe. We embrace the powerful positive impact autonomous transportation will bring to our everyday lives and with our ambition, we will become a leader in the development and operation of such vehicles. Thanks to our network, with hundreds of millions of rides every year, we have the means to make autonomy a safe reality. As a member of Level 5, you will have the opportunity to develop and deploy tomorrow’s hardware & software solutions and thereby revolutionize transportation.
As part of the Autonomy Team, you will be interacting on a daily basis with other software engineers and researchers to tackle some of the most challenging problems in AI, robotics, and computer vision. We work on a diverse set of problems ranging from solving optimization problems in 3D geometric computer vision, to minimizing latency on hardware accelerators, to designing novel neural network architectures.
The Autonomy team is looking for a deep learning expert to drive the research and deployment of the next generation of deep learning models for Autonomous driving. The ideal candidate will have published some deep learning research in top-tier conferences such as NeurIPs or CVPR, built and deployed real world deep learning products and worked in a fast-paced environment along with other highly talented engineers.Responsibilities:
- Work in a small, high-velocity team of engineers and researchers
- Develop a vision for the next generation of deep learning systems for the autonomous vehicle, taking into account many factors such as scalability, inference speed, and generalization power
- Be a champion of the scientific method and critical thinking in inventing state-of-the-art deep learning solutions but is also a leader in applying rigorous engineering practices during validation and deployment
- Collaborate closely with teams such as Planning, Simulation, Infrastructure, Tooling, and Hardware to drive a unified vision and roadmap
- Advance the state-of-the-art and represent Level 5 at top-tier conferences (e.g. CVPR, NeurIPs, ICCV, CoRL, ICRA)
- MS (PhD preferred) in Computer Vision, Machine Learning, Robotics, or other quantitative fields or relevant work experience
- Expertise in building deep learning systems with C++ and Python
- Programming experience implementing cutting-edge DeepLearning ML solutions using PyTorch / Tensorflow
- Understanding of ML workflow: preparing the data, implementing and training ML models, evaluating results, deploying inference on different platforms
- (Nice to have) Experience working on self-driving problems (Perception, Prediction, Mapping, Localization, Planning, Simulation)
- (Nice to have) Expertise (MS or PhD-level) in probabilistic modeling, high performance compute, dynamical systems, or computational geometry
- Great medical, dental, and vision insurance options
- Mental health benefits
- In addition to 12 observed holidays, salaried team members have unlimited paid time off, hourly team members have 15 days paid time off
- 401(k) plan to help save for your future
- 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
- Pre-tax commuter benefits
- Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program
Lyft is an equal opportunity/affirmative action employer committed to an inclusive and diverse workplace. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.