Solutions Engineer, Media

We’re hiring a Solutions Engineer for our media vertical to connect Protege’s media catalog with customer AI data needs. This is not a traditional modeling role. It is an applied data curation and delivery role for fast-moving, ambiguous environments where both speed and quality matter.

You will work with imperfect, evolving partner datasets and build strategies to normalize, validate, and operationalize them for downstream AI use cases. You’ll become an expert in Protege’s growing catalog of audio, video, and motion capture content — from longform assets with title-level metadata to clip-level content generated with TwelveLabs embeddings.

At a high level, you will understand what customers are building, identify the content that best fits their needs, and deliver datasets that meet both technical and conceptual requirements, often on tight timelines tied to active deals.

- Partner with Sales and Solutions to translate customer requirements into curation strategies

- Work with imperfect partner data, including mismatched metadata, schema differences, and incomplete labeling

- Normalize and standardize datasets for reliable downstream use

- Query and analyze Protege’s media catalog using SQL, internal APIs, and metadata tools to identify relevant content

- Build validation checks and workflows to ensure dataset integrity before delivery

- Identify, debug, and resolve data quality issues across file structures, metadata, and content alignment

- Use AI tools and transcoded embeddings to surface and refine clip-level content

- Turn messy, real-world data into structured datasets that meet customer and model requirements

- Run iterative sample reviews with customers, incorporate feedback, refine selections, and ensure final packages meet spec

- Build deep expertise in Protege’s media catalog structure, metadata, and growth patterns

- Track content coverage, diversity, and modality mix, and identify gaps relative to customer demand

- Partner with Product and Partnerships to share catalog insights that inform sourcing priorities

- Work cross-functionally to ensure content packaging meets technical, ethical, and licensing requirements

- Develop methods, scripts, and internal tools that improve curation efficiency and scale

- Help shape Protege’s delivery platform, including how internal users and customers search, sample, and export data

- Work closely with embedding-based systems to iterate between algorithmic selection and human review

- Define best practices for embedding queries, relevance evaluation, and content diversity

- Maintain a high bar for operational excellence and quality assurance throughout the process

- Build a working understanding of the media catalog, delivery lifecycle, and core tools.

- Establish strong cross-functional relationships and shadow live curation workflows.

- Lead dataset sampling and curation for active use cases, and document reusable workflows.

- Surface early insights on catalog coverage, metadata quality, and process improvements.

- Create repeatable QA and delivery workflows that increase consistency and speed.

- Provide actionable feedback that shapes platform, sourcing, and catalog roadmap decisions.

- 4-7 years of experience in data science, media analytics, technical curation, or similarly hands-on data roles.

- Strong SQL proficiency and comfort querying large, messy datasets to generate insight and action.

- Experience working with media metadata, embeddings, or unstructured content.

- Ability to translate nuanced customer or model requirements into concrete dataset specifications.

- High standard for data quality, operational rigor, and usability of delivered outputs.

- Clear communicator who can move between technical depth and customer-friendly clarity.

- Thrive in ambiguous, fast-moving environments and treats teammates with kindness.

- Familiarity with video/audio processing, embeddings, or multimodal AI workflows.

- Prior experience curating or packaging datasets for machine learning.

- Background in content analysis, recommendation systems, or information retrieval.