Join Suno as a Machine Learning Engineer to develop innovative recommendation models for music discovery.
Posted by employer 4 hours ago
First seen on Joblaze 2 hours ago
Last verified on the company career page 2 hours ago
Skills & Technologies
What you'll build
- Develop mathematical models of user preference
- Design learning systems for user taste inference
- Build and deploy scalable recommendation models
- Run large-scale experiments to evaluate models
- Define technical direction for personalization systems
Must have
- Strong background in applied mathematics or statistics
- Experience designing models from first principles
- Proficiency in Python and modern ML frameworks
- Familiarity with learning from user interaction data
- Comfort reasoning about model quality and scalability
Nice to have
- A love of music
Practical constraints
- Applicants must be eligible to work in the US
Requirements
- Experience
- 3+ years
- Education
- PhD
- Visa
- No sponsorship (stated in posting)
Not disclosed in this posting: compensation, work arrangement.
Benefits
Joblaze summary
In this role, the Machine Learning Engineer will focus on developing and deploying advanced recommendation models to enhance music discovery for users. Key skills include a strong foundation in applied mathematics and machine learning, proficiency in Python and frameworks like PyTorch, and experience with user interaction data. This position is ideal for someone with a PhD or equivalent experience who is comfortable making technical decisions and has a passion for music. The engineer will collaborate closely with the founding team, contributing to the personalization systems of a rapidly growing company.
Joblaze insights
- Listed today — first seen on Joblaze October 1, 2026. Last confirmed on Suno's careers page October 1, 2026.
- Python appears in 48.4% of 450 comparable mid ai/ml roles in United States; Statistics appears in 0.4% of 450 comparable mid ai/ml roles in United States.
Quick facts
- How much experience is required?
- At least 3 years of relevant experience for this Machine Learning Engineer - Content Discovery role.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: Applied Mathematics, Machine Learning, PyTorch, Python, Statistics.
- What seniority level is this role?
- Suno targets mid-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Machine Learning Engineer - Content Discovery role at Suno.
From the original posting
About the Role
We’re looking for early members of our machine learning recommendations team. You’ll work closely with the founding team and have ownership of a wide variety of technical decisions on how we build and deploy our state of the art recommendation models.
Machine Learning Recommendations Engineer Song Description
What You’ll 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 (relevance, novelty, diversity, 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 Suno’s personalization systems
What You’ll Need
Strong background in applied mathematics, statistics, machine learning, or a related quantitative field (PhD or equivalent experience)
Experience designing models from first principles (e.g., probabilistic models, optimization-based systems, representation learning, graph-based methods)
Proficiency in Python and modern ML frameworks (e.g., PyTorch) with the ability to implement and iterate on research ideas
Familiarity with learning from user interaction data (implicit feedback, ranking losses, bandits, or reinforcement-learning-adjacent methods)
Comfort reasoning about tradeoffs between model quality, scalability, and system constraints
Curiosity, rigor, and a desire to understand systems deeply rather than treating models as black boxes
A love of music (listening, exploring, or making) is a strong plus
Additional Notes: Applicants must be eligible to work in the US.
Perks & Benefits for Full-Time Employees
Company Equity Package
16 Weeks of Paid Parental Leave
Creative Education Stipend
Generous Commuter Allowance
In-Office Lunch (5 days per week)
Standard company text repeated across Suno's postings is omitted here.