Job offers - CrawlJobs

Content Engineer United States Jobs (On-site work)

3 Job Offers

New
Research Engineer, Content Understanding
Save Icon
Join Exa's applied AI lab in San Francisco as a Research Engineer for Content Understanding. Build large-scale document understanding models, judge page quality and credibility, and shape how search engines process the entire web.
Salary Icon
Salary
Not provided
exa.ai Logo
EXA
Expiration Date
Until further notice
New
Senior/Staff Machine Learning Engineer - Content Discovery
Save Icon
Suno seeks a Senior/Staff ML Engineer in San Francisco to build scalable recommendation and ranking systems for music discovery. Requires Python, PyTorch, and 0->1 production ML experience.
Salary Icon
Salary
Not provided
Suno
Expiration Date
Until further notice
Product Content Engineer
Save Icon
Join Instagram as a Product Content Engineer to drive GenAI-powered creative experiences. You’ll craft editorial guidelines, evaluate AI-generated images/videos, and collaborate with product teams to set quality standards. Requires 6+ years in content strategy, strong editorial judgment, and expe...
Salary Icon
Salary
131000.00 - 190000.00 USD / Year
meta.com Logo
Meta
Expiration Date
Until further notice

About the Content Engineer role

Content Engineer jobs represent a dynamic and rapidly evolving career path at the intersection of content strategy, data analysis, and artificial intelligence. Professionals in this role are responsible for bridging the gap between human expertise and machine learning systems, ensuring that digital products deliver relevant, high-quality, and scalable content experiences. Unlike traditional content roles, content engineering focuses on building the frameworks, datasets, and evaluation pipelines that power AI-driven ranking, recommendation, and moderation systems.

Typical responsibilities for content engineer jobs include developing and executing content strategies that improve product experiences for end users. This often involves working closely with engineering, product, and data science teams to define how content is discovered, distributed, and understood by algorithms. Content engineers frequently create and maintain golden datasets—curated collections of high-quality examples that serve as ground truth for training and benchmarking machine learning models. They design evaluation rubrics, conduct human evaluations of AI outputs, and calibrate automated judging systems to ensure consistency and accuracy.

A significant portion of content engineer jobs revolves around generative AI and large language models (LLMs). Professionals in this field write prompts, annotate content, analyze model behavior, and identify areas where AI systems fall short. They translate technical product needs into actionable content solutions, while also performing data analysis to test hypotheses and drive measurable business impact. Many content engineers also build lightweight automation scripts and internal tools using programming languages like Python, connecting data sources with AI models to streamline content production at scale.

The typical requirements for content engineer jobs include several years of experience in content strategy, content operations, or AI evaluation. Strong analytical skills are essential, as is the ability to work independently in fast-paced, ambiguous environments. Technical proficiency with Python, APIs, and modern AI platforms is increasingly important, along with experience in prompt engineering, annotation, and content labeling. Exceptional communication skills are necessary for presenting findings to both technical and non-technical stakeholders, while project management abilities help coordinate cross-functional initiatives.

Content engineer jobs appeal to professionals who enjoy solving complex problems at the nexus of language, technology, and user experience. They require a unique blend of creativity and technical rigor, with a focus on building systems that scale quality. As AI continues to reshape digital products, content engineers play a critical role in ensuring that these systems actually work for people, making this profession both challenging and highly rewarding.