Job description

Smule has been on a mission to bring the world together through music since 2008. Music is much more than listening… it's about creating, sharing, discovering, participating, and connecting with people. With dozens of millions of monthly active users creating over 20 million songs every day, Smule is connecting people all over the world through the joy of making music and transforming the music landscape from one of passive listening to collaborative creative expression and active engagement. About the Role We are hiring a Research Engineer to accelerate Smule's research teams by building the infrastructure, tooling, and experimental frameworks that make rigorous research possible at scale. You will work side-by-side with research scientists, turning experimental ideas into robust, reproducible code and helping bridge the gap between prototype and production. The ideal candidate is a skilled software engineer with genuine curiosity about ML research, deep systems knowledge, and a talent for making researchers more productive. We strongly encourage candidates with non-traditional backgrounds to apply. If your path into research engineering came through audio software development, game engine programming, embedded systems, HPC, or another field, we want to hear from you. What You'll Be Doing: Design, implement, and maintain research infrastructure including experiment tracking, distributed training pipelines, and evaluation frameworks. Collaborate with research scientists to implement, debug, and optimize novel model architectures, training procedures, and data pipelines. Build tooling and abstractions that accelerate the experiment-iterate-publish cycle for the research team. Ensure reproducibility of research results through rigorous version control of code, data, configurations, and compute environments. Profile and optimize training and inference performance across GPU clusters, identifying and resolving bottlenecks. Contribute to open-source projects and internal libraries that codify best practices and reusable components. What We're Looking For: Degree (B.S., M.S., or Ph.D.) in Computer Science, Software Engineering, Electrical Engineering, or a related technical discipline, or currently pursuing one. Strong proficiency in Python and experience with PyTorch, including custom modules, training loops, and distributed training (DDP, FSDP). Solid understanding of software engineering best practices: testing, CI/CD, code review, and documentation. Familiarity with Linux, GPU computing, and cloud or on-prem HPC environments. Ability to read and implement methods from ML research papers. Bonus Points For: Experience with audio, speech, or music signal processing pipelines. Familiarity with containerization (Docker) and orchestration (Kubernetes, Slurm). Contributions to open-source ML frameworks or research codebases. Smule is an Equal Opportunity Employer and considers all qualified applicants without regard to race, color, religion, sex, gender identity or expression, sexual orientation, national origin, ancestry, age, disability, medical condition, genetic information, marital status, military or veteran status, or any other protected characteristic under federal, state, or local law. We are committed to creating an inclusive environment for all employees and applicants. If you require a reasonable accommodation during the application or interview process, please let us know.

Requirements

Must-haves

Design, implement, and maintain research infrastructure including experiment tracking, distributed training pipelines, and evaluation frameworks.
Collaborate with research scientists to implement, debug, and optimize novel model architectures, training procedures, and data pipelines.
Build tooling and abstractions that accelerate the experiment-iterate-publish cycle for the research team.
Ensure reproducibility of research results through rigorous version control of code, data, configurations, and compute environments.
Profile and optimize training and inference performance across GPU clusters, identifying and resolving bottlenecks.
Contribute to open-source projects and internal libraries that codify best practices and reusable components.
Degree (B.S., M.S., or Ph.D.) in Computer Science, Software Engineering, Electrical Engineering, or a related technical discipline, or currently pursuing one.
Strong proficiency in Python and experience with PyTorch, including custom modules, training loops, and distributed training (DDP, FSDP).
Solid understanding of software engineering best practices: testing, CI/CD, code review, and documentation.
Familiarity with Linux, GPU computing, and cloud or on-prem HPC environments.
Ability to read and implement methods from ML research papers.
Experience with audio, speech, or music signal processing pipelines.
Familiarity with containerization (Docker) and orchestration (Kubernetes, Slurm).
Contributions to open-source ML frameworks or research codebases.
We are committed to creating an inclusive environment for all employees and applicants. If you require a reasonable accommodation during the application or interview process, please let us know.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

mlpythonci/cddockerkubernetes

Platform: bamboohr
Effort: medium