Staff Engineer, Autonomous Driving Data Platform & Curation

CARIAD, Inc., Mountain View, CA

The role

The Staff Engineer, Autonomous Driving Data Platform & Curation is a hands-on staff-level individual contributor who owns the path from raw multimodal vehicle data to reliable, versioned, and model-ready datasets. The ideal candidate combines production data or ML systems experience with practical knowledge of autonomous-driving data and can lead ingestion, schema, storage, query, curation, quality, and delivery. This engineer designs and operates datasets containing more than 10 million records or samples, evaluates formats such as Parquet and Lance, and enables efficient filtering, slicing, random access, and sequential retrieval.

All jobs

Staff Engineer, Autonomous Driving Data Platform & Curation

CARIAD, Inc., Mountain View, CA

Posted pay

$196K–$269K

a year

Compared with similar jobs

This base pay is near the median for staff infrastructure, platform and SRE jobs in the Bay Area.

Median: $242K a year
Other jobs in the group: 308

We compare the middle of each posted range. This is base pay as posted. The group does not include this job.

Location: Mountain View, CA
Work type: Not given
Level: Staff
Experience: 8+ years
Skills in the job text: Python
SQL
Spark
Airflow
Ray
Posted: Sep 11, 2026
Last check: 9 h ago
Job type: Infra, platform & SRE, Data engineering, Inference & ML systems, ML / AI engineering

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CARIAD, Inc.

Open tech jobs: 5
With posted pay: 100%

About CARIAD, Inc.: funding, hiring and pay

CARIAD, Inc.

About CARIAD, Inc.: funding, hiring and pay

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The role

What you need

General Skills

Deep production experience with Parquet and/or Lance, including dataset migration, indexing, compaction, schema evolution, version maintenance, cloud storage, random access, or training-loader optimization.
Experience with large-scale multimodal autonomous-driving data from cameras, LiDAR, radar, maps, localization, vehicle state, simulation, or other sensor-rich robotic systems.
Experience building auto-labeling, active-learning, model-in-the-loop, or human-in-the-loop systems, including confidence calibration, annotation routing, review workflows, audit sampling, label agreement, and annotation QA.
Strong statistical knowledge for quality monitoring, distribution comparison, drift measurement, anomaly detection, and out-of-distribution detection.
Experience using rule-based logic, geometry and metadata heuristics, embeddings, semantic search, VLMs, classifiers, or other learned methods to tag data, assess quality, mine edge cases, detect hard examples, or prioritize review.
Experience connecting dataset metrics, composition, label quality, drift, cost, and downstream model performance through dashboards and evaluation.
Experience optimizing distributed ML data loading, caching, sampling, preprocessing, and the data-to-GPU path.
Experience preparing sequential or trajectory datasets for imitation learning, offline reinforcement learning, preference or ranking data, reward modeling, or policy evaluation, including observations, actions, rewards, policy provenance, and replay semantics.
Familiarity with data governance, privacy, retention, redaction, access control, auditability, and security requirements for fleet-collected sensor data.

Required Specialized Skills

Demonstrated ownership of production data pipelines and large datasets, including systems with more than 10 million records or samples or comparable multi-terabyte scale.
Strong dataset and storage foundation, including schema design, columnar storage, partitioning, file and fragment sizing, compression, predicate pushdown, projection, indexing, compaction, schema evolution, versioning, lineage, and reproducibility.
Hands-on experience with Parquet, Lance, Apache Arrow, or a comparable analytical dataset technology, with the ability to reason about format selection and benchmark storage, query, update, and model-loading trade-offs.
Strong Python and SQL skills with production software-engineering practices, including testing, code review, version control, profiling, debugging, maintainable APIs, and operational documentation.
Experience building distributed or parallel data pipelines and orchestration using technologies such as Ray, Spark, Beam, Dask, Airflow, Dagster, or comparable systems.
Experience with local or cloud object storage, such as S3 or GCS, and practical understanding of throughput, request patterns, caching, data movement, reliability, access control, and cost.
Basic autonomous-driving or robotics data knowledge, including temporal sensor data, camera and other sensor modalities, timestamps and synchronization, calibration, ego and vehicle state, coordinate frames, clips, trajectories, scenarios, and annotations.
Ability to design automated data validation and observability and translate ML training, sampling, evaluation, and failure-analysis needs into reliable data products.

Desired Skills

Deep production experience with Parquet and/or Lance, including dataset migration, indexing, compaction, schema evolution, version maintenance, cloud storage, random access, or training-loader optimization.
Experience with large-scale multimodal autonomous-driving data from cameras, LiDAR, radar, maps, localization, vehicle state, simulation, or other sensor-rich robotic systems.
Experience building auto-labeling, active-learning, model-in-the-loop, or human-in-the-loop systems, including confidence calibration, annotation routing, review workflows, audit sampling, label agreement, and annotation QA.
Strong statistical knowledge for quality monitoring, distribution comparison, drift measurement, anomaly detection, and out-of-distribution detection.
Experience using rule-based logic, geometry and metadata heuristics, embeddings, semantic search, VLMs, classifiers, or other learned methods to tag data, assess quality, mine edge cases, detect hard examples, or prioritize review.
Experience connecting dataset metrics, composition, label quality, drift, cost, and downstream model performance through dashboards and evaluation.
Experience optimizing distributed ML data loading, caching, sampling, preprocessing, and the data-to-GPU path.
Experience preparing sequential or trajectory datasets for imitation learning, offline reinforcement learning, preference or ranking data, reward modeling, or policy evaluation, including observations, actions, rewards, policy provenance, and replay semantics.
Familiarity with data governance, privacy, retention, redaction, access control, auditability, and security requirements for fleet-collected sensor data.

Years of Relevant Experience

8+ years of experience in applied machine learning or deep learning
4+ years of experience reinforcement learning, computer vision, or AD/ADAS systems.
Strong candidates with equivalent industry experience will be considered

Required Education

Master’s in Computer Science, Robotics, Electrical Engineering, Applied Mathematics, or a related field

Desired Education

PhD in Computer Science, Robotics, Electrical Engineering, Applied Mathematics, or a related field

Staff Engineer, Autonomous Driving Data Platform & Curation

The role

Staff Engineer, Autonomous Driving Data Platform & Curation

The role

What you need

General Skills

Required Specialized Skills

Desired Skills

Years of Relevant Experience

Required Education

Desired Education

Autonomous Data Architecture, Storage & Query

Autonomous Dataset Lifecycle, Curation & Training Readiness

Data Quality, Statistics & Distribution Monitoring

Auto-Labeling, Closed-Loop Data Automation & RL Readiness

Cross-Functional Technical Leadership, Reliability & Cost

Pay and benefits

About CARIAD, Inc.

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CARIAD, Inc.

Compared with similar jobs

The role

The role

What you need

​General Skills

​Required Specialized Skills

​Desired Skills

​Years of Relevant Experience

​Required Education

​Desired Education

Autonomous Data Architecture, Storage & Query

Autonomous Dataset Lifecycle, Curation & Training Readiness

Data Quality, Statistics & Distribution Monitoring

Auto-Labeling, Closed-Loop Data Automation & RL Readiness

Cross-Functional Technical Leadership, Reliability & Cost

Pay and benefits

About CARIAD, Inc.

Similar jobs at other companies

Compared with similar jobs

General Skills

Required Specialized Skills

Desired Skills

Years of Relevant Experience

Required Education

Desired Education