Phd Research Intern, Computer Vision/Lidar (Fall 2019)

Lyft Palo Alto , CA 94306

Posted 3 months ago

At Lyft, community is what we are and it's what we do. It's what makes us different. To create the best ride for all, we start in our own community by creating an open, inclusive, and diverse organization where all team members are recognized for what they bring.

Lyft's mission has been to improve people's lives with the world's best transportation. And self-driving cars are critical to that mission: they can make our streets safer, cities greener, and traffic a thing of the past. That's why we started Level 5, our self-driving division, where we're building a self-driving system to operate on the Lyft network.

Level 5 is looking for creative problem solvers to join us to develop the leading self-driving system for ridesharing. Our team members come from diverse backgrounds and areas of expertise, and each has the opportunity to have meaningful improvement on the future of our technology. Our world-class software and hardware experts work in brand new garages and labs in Palo Alto, California, and offices in London, England and Munich, Germany. And we're moving at an incredible pace and servicing employee rides in our test vehicles on the Lyft app. Learn more at

As part of the Autonomy Group, you will collaborate with software engineers to tackle advanced AI challenges. Your work on the Perception team will initially involve interpreting sensor data from multiple modalities into a model of the world. For this position, we are looking for a PhD Research Intern who is passionate about data and applying computer vision/machine learning research to Lyft's autonomous vehicles.


  • You and your team will work on core perception algorithms such as sensor calibration, objection detection, tracking, segmentation, and state space estimation.

  • You will build indoor and outdoor calibration algorithms for camera, LiDAR, IMU and radar.

  • Develop segmentation and classification algorithms on LiDAR point cloud data.

  • Implement state-of-the-art CV models based on latest publications in computer vision, perception and machine learning.

  • Develop sensor fusion algorithms for radar, LiDAR, and vision modalities.

  • Participate in team advancement of tools and infrastructure to evaluate the performance of perception stack and track it over time.


  • Experience achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as CVPR, ICML, ICLR, ECCV/ICCV or NeuraIPS

  • Hands-on experience building computer vision/machine learning applications on camera using LiDAR, IMU and radar data.

  • Demonstrated production-quality Python or C++

  • Collaborate with internal partners and promote openness to new / different ideas

Minimum Requirements:

  • Pursuing a PhD degree or higher in Computer Science, Electrical Engineering, or a related field and returning to a degree program after completion of the internship

  • Available for a 4-6 month internship between September 1, 2019 and April 30th, 2020

  • Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment

Lyft is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. Lyft does not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender-identity, sexual orientation, disability, age, military or veteran status, or any other basis protected by applicable local, state, or federal laws or prohibited by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Pursuant to the San Francisco Fair Chance Ordinance and other similar state laws and local ordinances, and its internal policy, Lyft will also consider for employment qualified applicants with arrest and conviction records.

icon no score

See how you match
to the job

Find your dream job anywhere
with the LiveCareer app.
Mobile App Icon
Download the
LiveCareer app and find
your dream job anywhere
App Store Icon Google Play Icon

Boost your job search productivity with our
free Chrome Extension!

lc_apply_tool GET EXTENSION

Similar Jobs

Want to see jobs matched to your resume? Upload One Now! Remove
Machine Learning Scientist Computer Vision Autopilot

Tesla Motors

Posted 3 days ago

VIEW JOBS 8/19/2019 12:00:00 AM 2019-11-17T00:00 The Role As a member of the Autopilot Vision team you will research, design, implement, optimize and deploy models and algorithms that advance the state of the art in autonomous driving. A strong candidate will ideally possess at least one strong expertise in the following areas, and at least a basic familiarity in others. Responsibilities * Train machine learning and deep learning models on a computing cluster to perform visual recognition tasks, such as segmentation and detection * Develop state-of-the-art algorithms in one or all of the following areas: deep learning (convolutional neural networks), object detection/classification, tracking, multi-task learning, large-scale distributed training, multi-sensor fusion, etc. * Optimize deep neural networks and the associated preprocessing/postprocessing code to run efficiently on an embedded device Requirements * Solid understanding of linear algebra, algorithms, machine learning, optimization, numerical methods * Excellent Python coding, strong engineering practices, debugging/profiling skills, familiarity with multi-threaded programming * Experience with data science tools including Python scripting, numpy, scipy, matplotlib, scikit-learn, jupyter notebooks, bash scripting, Linux environment * Experience with at least one main stream deep learning frameworks, including TensorFlow, PyTorch, Caffe(2), MXNet * Experience with computer vision or robotics libraries (e.g., OpenCV, PCL, ROS) * Experience with CUDA/OpenCL, OpenGL a plus Tesla Motors Palo Alto CA

Phd Research Intern, Computer Vision/Lidar (Fall 2019)