Skydance Media

Audio Lead (Games)

Santa Monica, Los Angeles

Sponsorship not specified$125k-$165kDetected 77 days ago

BudgetingRecruitingUnreal EngineCommunicationCollaboration

About the role

Through creativity, collaboration, and trust, we empower our teams to push boundaries and turn bold ideas into experiences that resonate with fans around the world.
Do you want to craft games that challenge expectations and inspire players?

Plan, source, and supervise external audio partners, composers, voice talent, and vendors as needed.
Collaborate closely with design, engineering, and art leads to ensure audio is fully integrated into gameplay systems and production workflows.
Partner with engineering to establish best practices for implementation in Unreal Engine.
Create and maintain documentation, pipelines, and standards that support a sustainable and efficient audio workflow.
Own scheduling, budgeting, and resource planning for all audio-related work.
You will guide, mentor, and support the sound design teams, ensuring our audio deepens immersion, strengthens gameplay clarity, and enhances emotional impact.
Proven ability to manage vendors, contractors, composers, and voice production.
We are searching for an Audio Lead to join our core team developing a high-quality AAA single-player story- driven action-adventure game built using the Unreal Engine.

The annual salary range for this position in Los Angeles is $125,000 - $165,000.
The salary offered may vary based on the candidate's location, qualifications, experience and relevant expertise, among other factors.
The range indicated is for base salary only and does not reflect the total compensation package, including bonus, benefits, etc.

As Audio Lead, you will define the creative vision, technical direction, and production standards for all audio in the project.
Define and champion the overall audio vision, ensuring it aligns with the game's tone, narrative, and player experience goals.

This listing is sourced directly from Skydance Media's careers page and normalized into a canonical job model.