Product Manager, Fleet Simulation (Level 5)

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.

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.

Developing an autonomous vehicle is a complicated prospect.  We’re looking for an experienced product manager to develop our hybrid human/AV fleet simulator in close partnership with our engineering team.  You will be a bridge between our understanding of how our future vehicles move in the world and the decisions of today. If you enjoy working in a fast-paced, safety-critical environment and you’re great at creating solutions given minimal detail beyond complicated requirements, you might be the person we’re looking for!

Responsibilities:

  • Completely own your team's products, existing or new, from ideation, through development, to launch, growth and maintenance
  • Communicate clearly roadmaps, priorities, experiments, and decisions across a wide spectrum of audiences from partner teams to executive levels
  • Own Lyft Level 5’s fleet simulator
  • Conceptualise simulation framework and architecture
  • Build complex and detailed simulations from the ground up to dynamically model AV fleet operations (charging, cleaning, service etc.), driver and passenger movements, attributes and interactions
  • Co-architect with engineering simulation modules and automation of simulation-based optimization and analyses
  • Develop and necessary tests and analyses to validate simulation models and identify improvement opportunities
  • Deep dive into data to validate operational processes and assumptions
  • Guide visualization of simulation results to support strategic and operational decision making

Experience & Skills


  • 2+ years of academic or operational background in developing and optimizing large-scale multi-agent systems simulation models

  • Extensive knowledge of software development capabilities, preferably in Python, C++ or Java; knowledge of GoLang would be an advantage

  • Experience in software architecting and development of communication interfaces


Nice to Have:

  • Computer science degree and experience as an engineer preferred

  • Experience processing large amounts of data using Hive, Spark or similar technology

  • Knowledge of statistical programming in languages such as Python; and strong working knowledge in RDBMS such as PostgresQL or MySQL

  • Experience in developing agent-based mobility simulations

  • Experience in state-of-art routing algorithms


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, Lyft will also consider for employment qualified applicants with arrest and conviction records.


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