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Salary
≈ $67k – $110k per year (Estimated)
Location
In office (Warsaw)
Seniority
Staff · 7+ years exp

Confirmed on the employer's own hiring board on Oct 13, 2026. First seen by Alion on Jan 17, 2026.

Overview
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Waymo is an autonomous driving technology company headquartered in Mountain View, California, that develops the Waymo Driver and operates a fully autonomous ride-hailing service. It began in 2009 as the Google Self-Driving Car Project and is now part of Alphabet; the Waymo Driver has completed more than ten million rider-only trips and over 100 million autonomous miles on public roads across more than 15 US states. It hires software and machine learning engineers, perception and planning researchers, safety and field operations specialists, hardware sourcing staff and corporate roles, with large teams in Mountain View, San Francisco, New York and London.

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.

As a Technical Lead Manager (TLM) in the Release Evaluation team, you will be the strategic architect and people leader behind the modern execution backend for our evaluation infrastructure. This role is at the heart of Waymo’s safety mission: you will lead and build a high-caliber engineering team to develop the mission-critical modern infrastructure (leveraging modern workflow engines like Manifold Flows and scalable pipelines) that validates the Waymo Driver’s performance. You will balance technical deep-dives-optimizing distributed systems, ensuring high reliability, and driving adoption of the new backend-with the mentorship and strategic vision required to ensure our virtual testing infrastructure is scalable and efficient.

By guiding the development of our "virtual laboratory's" execution backend, you will directly accelerate the safe deployment of autonomous technology and ensure the long-term reliability of the entire fleet.

You will:

  • Define the roadmap for modernizing high-performance, low-latency pipelines that form the execution backend for massive-scale evaluation and simulation.
  • Grow and develop a team of engineers, fostering a culture of technical excellence, code health, and continuous learning.
  • Drive the operational excellence of our evaluation pipelines, ensuring the new backend architecture is highly reliable, efficient, and scalable.
  • Lead the migration and integration of legacy evaluation workflows into the new architecture, optimizing execution efficiency and resource utilization.
  • Ensure the long-term stability and health of production systems while championing developer experience and best-in-class software practices.
  • Partner with Data Science, Simulation, and Systems Engineering leads to translate complex evaluation requirements into robust, high-performance infrastructure solutions.

You have:

  • 5+ years of full-time software engineering experience (or a CS PhD with 2+ years of professional SWE experience).
  • 1+ years of prior management experience.
  • Advanced command of C++ (or another OOP language) with functional familiarity in Python and SQL.
  • A deep interest in autonomous driving, simulation-based evaluation, and large-scale data systems.

We prefer:

  • 7+ years of industry experience (or 3+ years post-doc) in building a large scale production system with its long term stability and health in mind.
  • 2+ years of management experience.
  • Proven track record as a Technical Lead, overseeing the full lifecycle of complex projects: from backend infrastructure design and performance optimization to data synthesis and production stability.
  • B.Sc., M.Sc., or PhD in Computer Science.
  • Experience architecting and managing FAANG-scale distributed systems, particularly those involving task orchestration, workflow engines, or pipeline execution.
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