Multimodal Data Engineer for AI Training Pipelines

Acestack; Dallas (TX); On-site; USD 100,000 - 140,000; Full time

Job summary

Acestack is seeking a Data Engineer in Dallas, TX to design, build, and maintain scalable data pipelines for camera, LiDAR, GNSS, IMU, and telemetry streams. The role emphasizes processing multimodal data and preparing high-quality AI training datasets.

You will implement data quality checks, metadata standards, and dataset versioning while collaborating with AI, annotation, and platform teams in an agile environment.

Qualifications

• 5+ years of data engineering experience.
• Experience processing unstructured multimodal data (video, images, LiDAR, GNSS, IMU, telemetry).
• Strong Python and SQL with distributed processing experience.
• Cloud data platforms, data lake/lakehouse, and workflow orchestration knowledge.
• Data quality, metadata, lineage, and reproducible pipelines.

Responsibilities

• Design, develop, and maintain scalable pipelines for camera, LiDAR, GNSS, IMU, and telemetry data.
• Normalize, synchronize, enrich, and package multimodal data for annotation and AI training.
• Implement automated checks for completeness, integrity, calibration, timestamps, formats, and dataset consistency.
• Create reusable data models, metadata standards, lineage, and dataset-versioning practices.
• Optimize pipeline performance, reliability, observability, and cost.
• Troubleshoot data defects and collaborate with AI, annotation, quality, and platform teams.
• Document technical designs, operating procedures, and handoffs.

Skills

Data engineering experience

Multimodal data processing

Python

SQL

Distributed data processing

Cloud data platforms

Data quality & lineage

Tools

Workflow orchestration tools

Version control

Job description

Acestack is seeking a Data Engineer in Dallas, TX to design, build, and maintain scalable data pipelines for camera, LiDAR, GNSS, IMU, and telemetry streams. The role emphasizes processing multimodal data and preparing high-quality AI training datasets.

You will implement data quality checks, metadata standards, and dataset versioning while collaborating with AI, annotation, and platform teams in an agile environment.