Company Overview:
We are building Protege to solve the biggest unmet need in AI — getting access to the right training data. The process today is time intensive, incredibly expensive, and often ends in failure. The Protege platform facilitates the secure, efficient, and privacy-centric exchange of AI training data.
Solving AI’s data problem is a generational opportunity. We’re backed by world-class investors and already powering partnerships with some of the most ambitious teams in AI. The company that succeeds will be one of the largest in AI — and in tech.
We’re a lean, fast-moving, high-trust team of builders who are obsessed with velocity and impact. Our culture is built for people who thrive on ambiguity, own outcomes, and want to shape the future of data and AI.
Role Overview
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.
What You’ll Do
Own data quality and curate media datasets
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
Be the catalog expert
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
Operate across product, data, and customer
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
Drive human-in-the-loop media search and curation
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
What Success Looks Like
30 days: Learn and get operational
Build a working understanding of the media catalog, delivery lifecycle, and core tools.
Establish strong cross-functional relationships and shadow live curation workflows.
60 days: Deliver and improve
Lead dataset sampling and curation for active use cases, and document reusable workflows.
Surface early insights on catalog coverage, metadata quality, and process improvements.
90 days: Scale and influence
Create repeatable QA and delivery workflows that increase consistency and speed.
Provide actionable feedback that shapes platform, sourcing, and catalog roadmap decisions.
What You Bring
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.
Bonus if you also have:
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.
Working with Protege
We move fast - thoughtfully. Speed matters in what we're building, but so does intention. We're biased toward action and always learning.
We're a lean, high-trust team. Everyone has real ownership. Clarity and autonomy drive our best work.
We take our work seriously, not ourselves. We solve hard problems with humility and celebrate wins - big and small.
We're kind, direct, and inclusive. We give feedback early and often, with the goal of helping one another grow.
We're builders at heart. Every person at Protege is hands-on, resourceful, and focused on creating momentum.
We grow fast - together. You'll be surrounded by people who care about impact, who challenge you to think bigger, and who are genuinely excited about what comes next.