Data Engineer/Senior Data Engineer

PlusAI, Inc.; Santa Clara (CA); Hybrid; USD 150,000 - 210,000; Full time

Benefits offered by this job

Catered free lunch, unlimited snacks

401(k) plan

Job summary

PlusAI, a Physical AI company pioneering AI-based virtual driver software for factory-built autonomous trucks, seeks engineers to own the data loop end to end. You will primarily use Python to build scalable data pipelines, geospatial analytics, evaluation frameworks, and LLM-powered automation, evaluating autonomy behavior and gating releases across fleet and simulations.

We welcome engineers from data engineering, analytics, geospatial, evaluation, or robotics backgrounds and value ownership,

Qualifications

• BS/MS/PhD in Computer Science, engineering, or a related field, or equivalent practical experience.
• Proficiency in Python with experience building scalable data processing systems or evaluation frameworks.
• Experience developing metrics and analyzing large-scale time-series, event, or geospatial data, including principled metric definitions, validation, and error analysis.
• Experience building LLM-powered or agentic workflows for data analysis, evaluation, or automation.
• Ability to solve open-ended technical challenges and communicate findings clearly to engineering and program stakeholders.
• Self-driven with a strong sense of ownership: a quick learner who is eager to take responsibility and drive projects forward end to end.

Responsibilities

• Define and compute driving performance metrics — covering safety, comfort, progress, interventions, and compliance — and build scalable pipelines that evaluate them across fleet and simulation data.
• Analyze road-test and simulation data to identify trends, regressions, and anomalies in autonomy behavior and turn findings into actionable insights for engineering teams.
• Build geospatial analytics over fleet driving data including map-matched metrics and route performance.
• Create data foundations and tooling for release management, including comparisons and gating criteria.
• Develop AI agentic workflows to triage detected issues at scale and propose fixes with evidence for engineering review.
• Ensure work aligns with the company's Quality Management System (QMS) requirements.

Skills

Python

Data processing

Geospatial analytics

LLM workflows

Time-series analysis

Education

BS/MS/PhD in CS or related field

Tools

Apache Spark

Airflow

Job description

PlusAI is a Physical AI company pioneering AI-based virtual driver software for factory-built autonomous trucks. Headquartered in Silicon Valley with operations in the United States and Europe, Plus was named by Fast Company as one of the World’s Most Innovative Companies. Partners including TRATON GROUP’s Scania, MAN, and International brands, Hyundai Motor Company, Iveco Group, Bosch, and DSV are working with Plus to accelerate the deployment of next-generation autonomous trucks. If you’re ready to make a huge impact and drive the future of autonomy, Plus is looking for talented individuals to join its fast-growing teams.

Knowing how well our virtual driver drives — and why it fell short — is what lets us ship with confidence. In this role, you will own that loop end to end: the metrics that quantify driving performance, the pipelines that compute them at fleet scale, the analysis that turns them into judgments about autonomy behavior — including where on the map that behavior changes — the data and tooling that gate software releases, and the agentic workflows that take a detected issue from triage to a proposed fix. You will work primarily in Python across large-scale data processing, geospatial analytics, evaluation frameworks, and LLM-powered automation. We welcome engineers from data engineering, analytics, geospatial, evaluation, or robotics backgrounds; prior autonomous-vehicle experience is helpful but not required.

We are open to candidates at either the Engineer or Software Engineer level. Level will be determined by experience, technical depth, scope of ownership, and demonstrated impact. You do not need experience with every technology in our stack; we value strong fundamentals, ownership, and the ability to learn.

Responsibilities:

Define and compute driving performance metrics — covering safety, comfort, progress, interventions, and compliance — and build the scalable pipelines that evaluate them consistently across fleet and simulation data

Analyze road-test and simulation data in depth to identify trends, regressions, and anomalies in autonomy behavior, and turn them into clear findings that engineering teams act on

Build geospatial analytics over fleet driving data: map-matched metrics, route and corridor performance, location-based clustering of events and issues, and geographic coverage analysis that shows where the virtual driver performs well and where it struggles

Build the data foundations and tooling for release management, including release-over-release comparisons, readiness and gating criteria, and traceable evidence supporting release decisions

Build AI agentic workflows that triage detected issues at scale — clustering and deduplicating failures, attributing root cause, routing to the right owners, and proposing fixes with supporting evidence for engineering review

Ensure that your work is performed in accordance with the company's Quality Management System (QMS) requirements and contribute to continuous improvement efforts

Required Skills

BS, MS, or PhD in Computer Science, engineering, or a related technical field, or equivalent practical experience

Proficiency in Python, with experience building scalable data processing systems or evaluation frameworks

Experience developing metrics and analyzing large-scale time-series, event, or geospatial data, including principled metric definitions, validation, and error analysis

Experience building LLM-powered or agentic workflows for data analysis, evaluation, or automation

Ability to solve open-ended technical challenges and communicate findings clearly to engineering and program stakeholders

Self-driven with a strong sense of ownership: a quick learner who is eager to take responsibility and drive projects forward end to end

Preferred Skills

Experience with distributed data processing such as Apache Spark, and workflow orchestration such as Airflow or Argo Workflows

Familiarity with LLM agent frameworks (e.g., LangChain, LangGraph, or similar) and prompt/tool-orchestration patterns

Experience with geospatial data and tooling, such as GIS formats, map matching, spatial indexing and joins, PostGIS, GeoPandas, or map-based visualization libraries

Experience with release engineering, quality gating, or automated regression detection

Experience with autonomous vehicles, robotics, or other safety-critical systems

Experience building dashboards or analytics interfaces that expose metrics to users

Work, learn and grow in a highly future-oriented, innovative and dynamic field.

Wide range of opportunities for personal and professional development.

Catered free lunch, unlimited snacks and beverages.

Highly competitive salary and benefits package, including 401(k) plan.