Av Deployment Engineer Jobs (NOW HIRING)

WhatYou'llDo (Responsibilities)

• Architect and implement metrics and analyses to introspect autonomous driving software performance atinterfaces across the autonomy stack; partner closely with autonomy developers and systems engineers.

• Design and implement analysis algorithms that summarize, aggregate, and cluster metrics produced by simulations and on-road runs of the autonomy stack.

• Propose and develop new statistical and ML methods to quantify performance andidentifypatterns of system and subsystem behavior across diverse scenes and operational domains.

• Develop and apply methods to introspect the operation of ML components in the autonomy stack, including evaluation ofperception, prediction, and planning models.

• Build andmaintainautonomyevaluationdashboards and interactive reports that provide clear, explainable insights (e.g., trend analysis, drift detection, scenario coverage) for development, verification, and leadership.

• Leverage vision-language models (VLMs) and large language models (LLMs), whereappropriate, to classify autonomy performance,identifycritical scenarios, and prioritize validation efforts, integrating human-in-the-loop review where needed.

• Maintain a high technical standard through thoughtful system design, code reviews, testing, observability, and adherence to software-engineering best practices.

• Interface with cross-organizational partners to articulate requirements, resolve handoff issues, and share best practices around evaluation, metrics, and experiment design.

Your Skills & Abilities(Required Qualifications)

• 5+ years of applied experience with robotics or autonomous systems software (e.g., sensors,perception, prediction, planning, or control), data analysis, ML evaluation, or autonomy analytics.

• 3+ years evaluating dynamic systems using numerical and/or ML approaches, including time-series data, state derivatives, dynamics, and interconnected subsystems.

• StrongproficiencydevelopingPythonin production team environments, including testing, performance, and code review.

• ProficiencywithPandas, NumPy, SciPy,and plotting/visualization libraries for large-scale data analysis and reporting.

• Comfort working withC++codebases, including reading, debugging, and instrumenting core algorithms.

• A strong curiosity to question anomalous data and systematically root-cause discrepancies.

• Demonstrated technical leadership, including driving architectural decisions, influencing cross-team designs, and owning complex features or services end-to-end.

• Bachelor's, Master's, or PhD inComputer Science, Robotics, Mechanical or Aerospace Engineering, Machine Learning, Data Science, or a related field, or equivalent practical experience

What Will Give You a Competitive Edge (Preferred Qualifications)

• Experience inautonomous driving or field robotics, including visualizing and interpreting results from simulation and field experiments.

• Experience evaluating robotics or AV systems usingsensor data(e.g., camera, lidar, radar) and large-scaletime-seriesanalysis.

• Strong intuition fordata visualizationand the ability to decompose high-dimensional metrics into clear, trustworthy, and consumable views for technical and non-technical audiences.

• Familiarity withstatistical modeling, experimental design, and hypothesistestingfor autonomy or simulation evaluation; fluency with Pandas, NumPy, SciPy, and visualization tools.

• ProficiencyinC++ and SQL; experience shaping logging, data schemas, and evaluation pipelines for large-scale autonomy testing and performance monitoring.

• Experience working withROS or similar robotics/IPC frameworks, log pipelines, and large-scale experiment databases or evaluation platforms.

• Prior development experience withcomputational geometry, linear algebra,PyTorch, and ML techniques applied toperception, prediction, planning, or control.

• Background in modelingagent interactionand contributing torelease gatingand safety decisions for autonomy systems.

• ExperienceleveragingAI-assisted development and analytics toolsto improve productivity and evaluation coverage.

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