What to Expect
Tesla Autopilot applies deep learning for autonomous driving at scale. Past features we've launched include Navigate on Autopilot (making lane changes and taking highway exits), Smart Summon (calling the Tesla to you in a parking lot without anyone in the vehicle), Stopping for Stop Signs and Traffic Lights, Radar Removal, and more than a dozen active safety features. Currently, we are working to release the Full-Self-Driving feature on city streets. The team actively collects massive datasets from Tesla Vehicles, creates ground truth of labeled images and videos, and deploys deep neural networks to our fleet of more than a million Tesla cars.
As a Project Manager, you will run the "data engine," the process by which we improve neural networks via human-in-the-loop datasets by leveraging Tesla's fleet. You will take ownership of the datasets of specific Computer Vision models (ex. traffic lights) and make them large, high quality, and diverse. You will identify neural network challenge cases, work with engineers to formalize requirements and deliverables, mobilize the Data Annotation team to label/verify/audit data, and close the loop by driving improvements in models via data. You will manage the diversity of datasets (what scenarios should get annotated), the ontology (how data should be labeled), and program success by organizing project goals/milestones/risks. The Autopilot Data Engine is the most crucial aspect of "pre-neural-network" development and has unlocked every major Autopilot customer release.
What You'll Do
Manage Data Engine programs and associated projects from ideation to planning, pilot, and production
Collaborate with neural network engineers to triage areas where neural networks are challenged and should be improved via data
Write data queries to find more examples of issues or interesting, diverse, and plentiful data from our fleet to improve neural networks
Design annotation ontology with engineers, considering the implications for training neural networks
Partner with the data annotation leadership team to set goals, forecast timelines, and ensure goals are met
Design and define requirements for labeling interfaces by creating and testing core features, flagging issues, and prioritizing feature requests
Dive into the details including annotating data yourself
Communicate project progress, risks, and successes to stakeholders
Identify process inefficiencies and improve workflows with Autopilot Leadership, Program Management, and Engineering teams
What You'll Bring
Two+ years of industry experience in product, program, or project management or engineering
BS in Computer Science, Physics, Computer Engineering, or Electrical Engineering or proof of exceptional skills in related fields or practical software engineering experience
Coursework in machine learning and a strong understanding of deep learning fundamentals (training vs. test set, overfitting, precision/recall, positive supervision, etc.) to design neural network ontology
Familiarity with Python and Pytorch is a plus
Excellent work ethic, communication, attention to detail, and collaboration skills.
Ability to thrive in a constantly changing environment with high ambiguity
Passion for the future of transportation and autonomous technologies