AI Engineer — Classifiers, Media Intelligence & Voice R&D

Job Description

• Design, train, and deploy classification models across Studio’s content pipeline (style detection, quality scoring, semantic categorization, filtering, moderation signals)
• Build automated tagging and organization systems for our media library
• Attribute extraction and feature detection
• Clustering and similarity grouping
• Intelligent search and discovery signals
• Create and maintain training data pipelines
• Dataset curation and QA
• Annotation workflows and tooling
• Active learning loops to improve labeling efficiency and model performance
• Lead voice/audio R&D by evaluating frontier voice models (TTS, voice cloning, audio synthesis)

and prototyping integrations and define a practical path from research → production features

• Research and prototype image intelligence capabilities relevant to avatars and media tools: face/body analysis, pose estimation, image-to-image consistency and visual similarity, and style understanding
• Build evaluation frameworks to track classifier accuracy and calibration as well as model drift and performance over time
• Optimize inference for cost and latency (batching, quantization, caching, serving strategy)
• Integrate with GPU infrastructure and ship models behind production APIs, with monitoring and operational discipline

Tech Stack:
Python, PyTorch, GPU compute clusters (EOK), REST/webhook APIs, Type Script (NestJS integration), Postgre

SQL (labels/metadata), Redis, Temporal (pipeline orchestration)

• 3+ years building and deploying ML systems in production, especially classification / tagging / content understanding
• Hands‑on model training experience (not just API usage): curated datasets, tuned hyperparameters, debugged training runs, and shipped the result
• Strong background in computer vision (CNNs, ViTs, CLIP‑style embeddings, or similar)
• Demonstrable interest or experience in voice/audio AI (TTS, voice cloning, audio classification, speech synthesis) — production work, research, or serious side projects all count
• Proficiency in Python with PyTorch (or Tensor Flow) and comfort reading/adapting research code
• Experience building labeling pipelines, annotation processes, or active learning systems
• Understanding of production model serving: REST APIs, batching, latency constraints, monitoring, and drift detection
• Familiarity with embeddings, vector search, or semantic similarity systems for retrieval/discovery features — experience with diffusion models, GANs, or generative audio techniques
• Experience publishing research, open‑sourcing ML tooling, or contributing to ML community work

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances.

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