AI Engineering Lead
Leads a hands-on AI engineering team developing, evaluating, and deploying large-scale multimodal and video models. The role combines post-training, inference optimization, product experimentation, technical roadmap ownership, and people management.
About the job
Responsibilities
- Ship AI/ML models from prototype to production at scale.
- Build data flywheels that convert user behavior and feedback into training data and continuous model improvements.
- Optimize inference for self-hosted models, including latency, throughput, GPU utilization, quantization, and serving cost.
- Evaluate models using offline benchmarks, human evaluation, online experiments, and product-quality metrics.
- Apply LLMs and multimodal models to video applications such as highlight detection, content curation, ranking, personalization, and editing decisions.
- Make build-versus-buy decisions across proprietary APIs, open-source models, and internally trained models.
- Set the technical roadmap, review architecture, mentor engineers, and manage a small AI team.
- Balance model quality, latency, reliability, and infrastructure cost.
Requirements
- Proven experience shipping AI/ML models from prototype to production at scale.
- Deep expertise in model post-training, including fine-tuning, preference optimization, evaluation, and learning from user feedback.
- Strong inference optimization experience for self-hosted models.
- Strong model evaluation skills.
- Practical experience applying LLMs or multimodal models to video applications.
- Familiarity with video-related models and systems, including vision-language models, ASR/transcription, video understanding, and enhancement/upscaling.
- Ability to set technical roadmaps, review architecture, mentor engineers, and manage a small high-performing AI team.
- Product-oriented and pragmatic approach to model quality, latency, reliability, and infrastructure cost.
Nice to Have
- Experience with consumer video, creator tools, recommendation or content systems, or other high-scale multimodal products.
Skills
Ai/Ml Models, Model Fine-Tuning, Preference Optimization, Model Evaluation, LLMs, Multimodal Models, Inference Optimization, Quantization, Gpu Utilization, Vision-Language Models, Asr, Video Understanding, Recommendation Systems, Personalization
Similar jobs
ML Engineering jobs
Discord
United States
Leads Discord’s Safety ML team, setting technical direction and overseeing production machine learning systems for content understanding, account integrity, and platform abuse. Requires substantial machine learning and engineering management experience, hands-on technical depth, and experience delivering ML systems at scale.
OpenAI
San Francisco, CA
Build production machine learning systems for model customization, post-training, evaluation, and AWS-native API integration. The role requires 7+ years of relevant engineering experience and expertise in deep learning, transformers, LLM fine-tuning, and production ML infrastructure.
Garner Health
New York, NY
Leads and builds a team of Applied Scientists developing production algorithmic systems for healthcare optimization, LLM applications, and member engagement. Requires 6+ years of relevant industry experience, strong technical judgment, and hands-on expertise across machine learning and optimization.
Baselayer
San Francisco, CA
Senior AI Engineer responsible for production LLM agents that enrich business identity data through web discovery, verification, classification, and risk scoring. The role requires strong asynchronous Python, agent and evaluation expertise, browser automation, and experience operating AI systems in production.
Otter
Mountain View, CA
Leads the development and production deployment of large-scale ASR and TTS systems for conversational intelligence products. The role requires 5+ years of industry experience, deep speech-model expertise, and strong software engineering and ML operations capabilities.