Senior/Staff Machine Learning Engineer - Content Discovery
About this role
Developing advanced recommendation and ranking models that operate under strict latency constraints forms the core daily activity for engineers on this team. Team members formulate mathematical models of user preference and design learning systems to infer taste from sparse interaction data, while collaborating closely with product leadership to shape personalization strategy.
Suno operates a consumer creative entertainment platform focused on music generation, backed by prominent investors and serving a massive user base ranging from casual creators to professional artists. The engineering group tackles complex problems at high speed, requiring high personal ownership and an appreciation for quality. Candidates who thrive in this environment typically possess deep technical rigor, a strong foundation in applied quantitative fields, and a genuine enthusiasm for music.
What you will do
- Formulate and develop mathematical models of user preference, similarity, and engagement for music discovery.
- Design learning systems that infer user taste from sparse, noisy, and evolving interaction data.
- Build and deploy scalable recommendation and ranking models that operate under real-time latency and throughput constraints.
- Translate abstract objectives like relevance, novelty, diversity, and long-term satisfaction into measurable metrics and optimized systems.
- Run large-scale experiments and causal analyses to evaluate model behavior and product impact.
- Work closely with product and research leadership to define the technical direction of personalization systems.
What you need
- Hold a strong background in applied mathematics, statistics, machine learning, or a related quantitative field through a PhD or equivalent experience.
- Demonstrate experience designing models from first principles such as probabilistic models, optimization-based systems, representation learning, or graph-based methods.
- Show proficiency in Python and modern machine learning frameworks like PyTorch, with the ability to implement and iterate on research ideas.
- Bring familiarity with learning from user interaction data including implicit feedback, ranking losses, bandits, or reinforcement-learning-adjacent methods.
- Display comfort reasoning about tradeoffs between model quality, scalability, and system constraints.
- Exhibit curiosity, rigor, and a desire to understand systems deeply rather than treating models as black boxes.
Nice to have
- A love of music (listening, exploring, or making)
Benefits
- Company Equity Package
- 401(k) with 3% Employer Match & Roth 401(k)
- Medical, Dental, & Vision Insurance (PPO w/ HSA & FSA options)
- 11 Paid Holidays + Unlimited PTO & Sick Time
- 16 Weeks of Paid Parental Leave
- Creative Education Stipend
Skills and tech stack
Questions candidates ask
What is the location for this role?
The position is based in San Francisco. Applicants must be eligible to work in the US.
What compensation and equity are offered?
The salary ranges from $241,200 to $382,935 and includes an offers equity package. Additional financial benefits include a 401(k) with a 3% employer match and Roth 401(k).
What technologies will I be working with?
Engineers work with Python and modern machine learning frameworks like PyTorch. The work involves building scalable recommendation and ranking models under real-time latency and throughput constraints.
What benefits are provided for full-time employees?
Full-time employees receive medical, dental, and vision insurance with PPO, HSA, and FSA options. Other perks include 11 paid holidays, unlimited PTO and sick time, 16 weeks of paid parental leave, a creative education stipend, a generous commuter allowance, and in-office lunch five days per week.