Build and maintain a self-service fleet simulation environment for data scientists and ML engineers to test and evaluate autonomous vehicle orchestration algorithms (dispatch, routing, assignment). Requires production Python experience and building tools for non-specialists.
191k – 266k/yr
On-siteData Engineering
About the role
Responsibilities
Turn existing fleet-simulation components into a coherent, self-service environment that data scientists and ML engineers can run without deep software expertise.
Fill gaps and build the connective tissue between simulation, data, and fleet-orchestration algorithms.
Build generalizable mechanisms that let teams measure how their orchestration algorithms affect fleet efficiency.
Collaborate with data science, ML, and fleet-orchestration teams to shape and prioritize the simulation roadmap.
Establish best practices and processes around simulation, evaluation, and data-driven decision-making.
Requirements
Software development experience in a production environment, with fluency in Python (or demonstrated experience learning new programming languages).
Experience building tools, services, or frameworks that make complex systems usable by non-specialist users.
Familiarity with any version control system (preference for Git).
Experience designing metrics and building mechanisms that deliver robust, actionable insights.
Good communication and collaboration skills.
Nice-to-Haves
Basic familiarity with C++ and/or Kotlin.
Experience with microservices and/or distributed systems.
Experience with simulation and/or fleet orchestration (dispatch, routing, vehicle assignment).
Architect and build foundational data infrastructure for massive simulation outputs. Design novel data models and high-throughput pipelines to feed LLMs with structured context from complex, state-based environments.
186k – 233k/yr
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