Multimodal AI Engineer – Image/Video & Audio

Maven Ventures; Palo Alto (CA); In loco; USD 180.000 - 440.000; Tempo pieno

Vantaggi offerti da questo lavoro

Equity

Medical coverage

Vision coverage

Dental coverage

401(k) retirement plan

Disability insurance

Life insurance

Employee discounts

Descrizione del lavoro

SpaceXSI is building a comprehensive AI stack focused on multimodal capabilities across image, video, and audio. The Imagine Model Team develops cutting-edge experiences, spanning data curation, modeling, training, and production integration to deliver high-fidelity understanding and generation.

You will work closely with product teams to push model frontiers, optimize end-to-end experiences, and contribute to a dynamic, scalable research-to-product workflow in a highly collaborative environment.

Competenze

• Experience designing data-driven experiments and evaluating results.
• Experience building and maintaining large-scale ML systems.
• Strong collaboration with product and engineering teams.

Mansioni

• Drive multimodal capabilities for image and video generation and understanding.
• Improve data quality through annotation, filtering, augmentation, and synthesis.
• Design evaluation frameworks and reward models for quality.
• Implement efficient algorithms for real-time inference and scalable serving.
• Develop pipelines for multimodal datasets (image/video).
• Collaborate with product teams to deploy AI solutions.

Conoscenze

Data-driven experimentation

Distributed ML systems

Strong communication

Cross-functional collaboration

Strumenti

Python

JAX/XLA

PyTorch

Rust/C++

Spark

Ray

Descrizione del lavoro

SpaceXSI is building a comprehensive AI stack focused on multimodal capabilities across image, video, and audio. The Imagine Model Team develops cutting-edge experiences, spanning data curation, modeling, training, and production integration to deliver high-fidelity understanding and generation.

You will work closely with product teams to push model frontiers, optimize end-to-end experiences, and contribute to a dynamic, scalable research-to-product workflow in a highly collaborative environment.