ML Engineer – Music Discovery & Real-Time Recommendations

Candidate; San Francisco (CA); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Company Equity Package

401(k) with Employer Match

Medical, Dental, & Vision Insurance

11 Paid Holidays + Unlimited PTO

16 Weeks Paid Parental Leave

Education Stipend

Generous Commuter Allowance

In-Office Lunch

Job summary

Suno is building the world’s first creative entertainment platform, enabling everyone to make music. We seek early ML engineers for our recommendations team to own models from formulation to deployment, collaborating with leadership to shape Suno’s personalization systems.

You will build scalable models, work on real-time latency constraints, and translate objectives into measurable metrics while enjoying a music-oriented, fast-paced environment.

Qualifications

• PhD or equivalent in a quantitative field.
• Experience designing models from first principles.
• Proficiency in Python and PyTorch.
• Familiarity with learning from user interaction data.
• Ability to balance model quality with scalability and system constraints.

Responsibilities

• Formulate and develop mathematical models of user preference, similarity, and engagement for music discovery.
• Design learning systems that infer user taste from sparse, noisy data.
• Build and deploy scalable recommendation and ranking models under real-time constraints.
• Translate objectives into measurable metrics and optimized systems.
• Run large-scale experiments and causal analyses to evaluate model behavior and product impact.
• Collaborate with product and research leadership to define technical direction of Suno’s personalization systems.

Skills

Applied mathematics

Statistics

Machine learning

Python

PyTorch

Research experience

Education

PhD or equivalent experience

Tools

PyTorch

Job description

Suno is building the world’s first creative entertainment platform, enabling everyone to make music. We seek early ML engineers for our recommendations team to own models from formulation to deployment, collaborating with leadership to shape Suno’s personalization systems.

You will build scalable models, work on real-time latency constraints, and translate objectives into measurable metrics while enjoying a music-oriented, fast-paced environment.