Senior ML Engineer: Lead Multimodal AI Systems

Twenty80 LLC; San Francisco (CA); On-site; USD 140,000 - 210,000; Full time

Job summary

Twenty80 LLC seeks a Senior ML Engineer in San Francisco to build and scale AI systems used daily by many users. You will own ML projects end-to-end, from research through deployment and iteration, and develop multimodal models across video, text, images, and audio.

You’ll work with LLMs and external AI APIs to create content understanding models and semantic search capabilities, while maintaining robust MLOps and collaborating with product teams for impactful outcomes.

Qualifications

• 4–8 years of ML engineering experience, including production model deployment.
• Proficient in Python and core ML concepts with clean, maintainable code.
• Experience building end-to-end ML pipelines: data handling, training, deployment, monitoring.
• Comfortable working with LLMs and AI APIs in production.
• Expertise across NLP, computer vision, and audio processing.
• Product-focused, identifying ML opportunities to solve user problems.

Responsibilities

• Own ML projects end-to-end: research, prototyping, training, deployment, and iteration.
• Build multimodal ML systems for video, text, images, and audio data.
• Develop applications using LLMs and AI techniques like Retrieval-Augmented Generation (RAG).
• Create models for content understanding across text and visual media.
• Build search and discovery systems using semantic embeddings and retrieval methods.
• Develop audio analysis pipelines.
• Maintain and optimize MLOps infrastructure: data pipelines, model serving, monitoring, experiment tracking.
• Collaborate with product teams to translate requirements into deployable ML solutions.

Skills

Python

ML fundamentals

End-to-end ML pipelines

LLMs / AI APIs

NLP

Computer Vision

Audio processing

Product thinking

Tools

MLflow

AWS

GCP

Vector databases

Job description

Twenty80 LLC seeks a Senior ML Engineer in San Francisco to build and scale AI systems used daily by many users. You will own ML projects end-to-end, from research through deployment and iteration, and develop multimodal models across video, text, images, and audio.

You’ll work with LLMs and external AI APIs to create content understanding models and semantic search capabilities, while maintaining robust MLOps and collaborating with product teams for impactful outcomes.