Data Engineering Specialist – AI

The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.

Company Overview

A technology consulting and software development organization delivers cloud, artificial intelligence, data, and enterprise solutions across the United States. The organization provides opportunities for professionals to work on modern technology initiatives while supporting career development and growth within an established technology environment.

The organization is seeking a Data Engineering Specialist – AI to build and operate large-scale data systems that support modern AI training and evaluation pipelines. The role combines advanced data engineering expertise with a strong understanding of AI workloads, focusing on data ingestion, transformation, quality assurance, lineage, and high-throughput delivery to training jobs across diverse data modalities.

The successful candidate will have experience operating large-scale, potentially petabyte-scale data systems, strong software engineering fundamentals, and a clear understanding of how data infrastructure decisions can affect model quality and training efficiency.

Key Responsibilities

• Build and operate large-scale data infrastructure supporting AI training and evaluation workflows.
• Develop reliable data ingestion and transformation pipelines for high-volume datasets.
• Implement processes for data quality assurance, validation, and lineage.
• Support high-throughput delivery of data to AI and machine learning training jobs.
• Design and maintain scalable data systems capable of handling petabyte-scale workloads.
• Collaborate with engineering and AI teams to ensure data infrastructure meets model training requirements.
• Apply strong software engineering practices to data infrastructure development.
• Optimize data pipelines and systems to improve training efficiency and overall data quality.
• Support datasets across diverse modalities and large-scale AI workloads.
• Contribute to the continuous improvement of data infrastructure and pipeline reliability.

Required Qualifications

• 6+ years of professional data engineering experience, including significant experience supporting machine learning or AI workloads.
• Strong proficiency in Python.
• Proficiency in at least one JVM or systems programming language.
• Deep experience with modern data processing frameworks such as Spark, Ray, or Beam.
• Hands-on experience operating petabyte-scale storage and data pipeline systems.
• Strong understanding of data engineering principles and large-scale distributed systems.
• Experience designing and maintaining reliable, scalable data infrastructure.

Preferred Qualifications

• Experience working with large-scale multimodal datasets.
• Familiarity with data quality tooling and dataset evaluation methodologies.
• Exposure to privacy-preserving data systems and regulated data handling.
• Contributions to open-source data infrastructure projects.
• Experience supporting frontier model training pipelines.
• Strong understanding of AI training data requirements and infrastructure.
• Experience optimizing data systems for large-scale machine learning workloads.

Eligibility

• U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply.
• New H-1B visa sponsorship is not available for this position.

Disclaimer

SpringCube curates tech job listings from various company websites to support tech professionals globally.

1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
2. No Client Relationship: This company is not a client of SpringCube unless stated.
3. To Apply: Click the Apply button to be redirected to the hiring company’s application page for this job.
4. No Liability: SpringCube is not liable for inaccuracies.