Software Engineer, Backend

Waymo|23 Jan 2026

fulltimeonsite

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Listed location: Warsaw, Masovian Voivodeship, Poland

Work arrangement: onsite. A remote label does not confirm worldwide eligibility or visa sponsorship.

Read the employer’s description for qualifications, compensation and work eligibility. Confirm the position is still open on the application page.

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Job Description

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.

The RO Performance team is at the heart of understanding and improving Waymo's self-driving technology. We build and maintain the critical infrastructure, to process and analyze vast amounts of data from both real-world driving logs and simulations.

Our systems generate key metrics and power dashboards which are essential for tracking the product performance, identifying areas for improvement, and making data-driven decisions. The insights produced by our team directly influence Waymo's operational rollouts, weekly performance reviews, and ultimately, the safety and reliability of our autonomous vehicles.

In this hybrid role, you will report to an Staff Software Engineer.

You will:

Infrastructure & Pipeline Engineering: Design and operate high-performance, low-latency data pipelines for both massive-scale simulation and real-world monitoring.
Evaluation Fidelity: Improve the signal quality of driving tests by ensuring simulation results are highly predictive of real-world behavior and implementing metrics to measure simulation accuracy.
ML Integration: Deploy and potentially contribute to ML models that identify "interesting" driving scenarios, optimizing the efficiency of testing through robust integrations with large-scale models.
Software Excellence: Champion code health and developer experience by applying best practices to the simulation and monitoring ecosystems.
Cross-Functional Collaboration: Partner with Data Scientists and Systems Engineers to translate complex vehicle telemetry into actionable insights regarding the Waymo Driver's internal logic.

You have:

5+ years of full-time software engineering experience, or a quantitative PhD with 2+ years of professional software engineering experience
C++ (or another OOP language) proficiency
Python familiarity
SQL familiarity
Excited about autonomous driving, Simulation + Eval

We prefer:

7+ years of industry experience or 3+ years post-doc experience in a quantitative- or quality- focused engineering role in which you had experience as a technical lead for a team in which you were performing tasks like developing hypotheses, designing and running experiments, processing data from experiments, synthesizing conclusions, and ensuring the long term stability and health of the production system.
B.Sc., M.Sc. or PhD in Computer Science
Experience working with large FAANG scale distributed systems.

Skills mentioned

PythonSQLC++Distributed Systems

Frequently asked questions

Is the Software Engineer, Backend position at Waymo remote?

The Software Engineer, Backend role at Waymo does not have a confirmed remote arrangement in our data. Check the employer description for its work location.

What type of employment is the Software Engineer, Backend role?

Waymo is hiring for a full-time Software Engineer, Backend position.

Which skills are mentioned for the Software Engineer, Backend job at Waymo?

Detected skill labels include Python, SQL, C++, Distributed Systems. Check the employer description to distinguish required skills from preferred experience.