Research Engineer

Accountabilities: As a Research Engineer, you will take ownership of developing automated data quality systems that enable scalable and reliable AI training workflows. You will combine technical investigation, research, and engineering execution to identify challenges, build solutions, and continuously improve verification processes.

Analyze data quality issues, including inconsistencies, formatting challenges, ingestion problems, and other failure modes.

Perform hands-on data reviews to understand underlying quality issues and identify opportunities for automation.

Design and build scalable quality assurance systems using rule-based methods, AI-driven approaches, and automated evaluation techniques.

Develop hybrid verification workflows that effectively combine automation with human-in-the-loop review when needed.

Research and implement new approaches to improve data validation as AI technologies and data requirements evolve.

Own complex, open-ended technical problems from exploration through implementation and optimization.

Requirements:

The ideal candidate is a highly technical and curious engineer who can operate independently in a rapidly evolving AI environment. You should be comfortable exploring unclear problems, learning quickly, and building practical systems that address real-world data challenges.

Strong technical background with the ability to quickly learn and adapt in a fast-changing AI landscape.

Experience in AI/ML engineering, software engineering, or a similar technical role within an AI-focused environment.

Proven experience working with data ingestion, processing pipelines, or large-scale data systems.

Ability to reason about potential data quality issues using first-principles thinking.

Strong ownership mindset with the ability to manage ambiguous projects from concept to completion.

Experience working with noisy, unstructured, or complex datasets is a plus.

Understanding of when to apply automation versus human-in-the-loop approaches is preferred.

Willingness to collaborate in a high-impact, fast-paced environment.

Benefits:

Competitive base salary range of $140,000–$250,000 USD, depending on experience and qualifications.

Equity participation opportunities.

Fully remote work model within the United States.

Opportunity to solve challenging AI infrastructure problems with significant business impact.

High ownership and autonomy in shaping technical solutions.

Exposure to cutting-edge AI data workflows and emerging technologies.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether? 

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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