At Lyft, our mission is to improve peoples lives with the worlds best transportation. To do this, we start with our own community by creating an open, inclusive, & diverse organization.
We care deeply about delivering the best transportation experience; this means the best experience for the passenger & 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 & with our ambition, we will become a leader in the development & 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 & deploy tomorrows hardware & software solutions & thereby revolutionize transportation.
As part of the Autonomy Team, you will be interacting on a daily basis with other software engineers to tackle highly advanced AI challenges. Eventually, we expect all Autonomy Team members to work on a variety of problems across the autonomy space; however, with a focus on planning & control, your work will initially involve taking the output from the perception & localization systems to determine a short, medium, & long-term course of action. For this position, we are looking for a software engineer with a strong level of expertise in AI or robotics who deeply understands autonomous vehicles.
- Work on core planning & control algorithms such as routing, behavior planning, trajectory planning, feedback controllers, etc
- Develop state-of-the-art algorithms for planning under uncertainty
- Develop state-of-the-art methods that leverage machine learning & large scale data for motion planning
- Develop a behavioral reasoning framework to support navigation in complex traffic scenarios, such as lane changes, merges, double-parked vehicles, & blind turns
- Develop functionally safe systems that fail gracefully & safely exit traffic when difficult situations arise
- Implement real-time algorithms on CPU/GPU in C++
- Leverage state of the art machine learning frameworks like PyTorch to train machine learned motion planning components
- Build tools & infrastructure to verify & evaluate the performance of the planner/controller over time
- Ability to produce production-quality C++ & Python code
- Strong background in planning, predictions, machine learning, robotics, algorithms, model predictive control, vehicle dynamics, & data structures
- Ability to build applications for robot motion planning using a broad range of tools such as numerical optimization, machine learning, feedback control, system modeling, etc
- Ability to develop safety-critical planning systems for low-latency compute platforms
- Bachelor's degree or higher in Computer Science, Electrical Engineering, Robotic, Mechanical Engineering, Aerospace Engineering, Math, or related field
- Ability to work in a fast-paced environment & collaborate across teams & disciplines
- (Nice to Have) Hands-on experience with building a planning stack for mobile robots, from high-level route planning on road graphs & behavioral reasoning to trajectory optimization & low-level feedback control
- (Nice to Have) Experience with robot motion planning techniques like trajectory optimization, sampling-based planning, model predictive control, etc
- (Nice to Have) Experience with traffic agent intention modeling
- (Nice to Have) Experience with GPU programming in CUDA or OpenCL
- (Nice to Have) Experience with Machine Learning Frameworks like PyTorch or TensorFlow