Senior Machine Learning Engineer

Moises is a Series A music-tech company with over 70 million users across 190+ countries, named Apple’s iPad App of the Year in 2024. We build tools for musicians and producers that support creative work in real, practical ways. The focus is using technology to extend human creativity, not automate it away.

Job Summary

We are seeking an experienced Senior ML Engineer to lead the design and implementation of a robust ML infrastructure that enables efficient model training, optimization, and deployment. You will also be responsible for bridging the gap between research and production, ensuring our machine learning models are production-ready and operate reliably at scale across diverse environments.

What you’ll do

ML Infrastructure & Training

• Design and implement scalable data pipelines and training infrastructure for machine learning models
• Optimize data loading and processing systems to support efficient model training
• Collaborate with research teams to productionize experimental models and scale them for production use

Model Optimization & Deployment

• Build deployment strategies for models across edge devices and cloud platforms
• Optimize models for production environments using industry-standard frameworks and conversion tools
• Ensure models meet performance, latency, and resource requirements across different hardware platforms

Automation & CI/CD

• Develop and maintain automated testing, deployment, and monitoring pipelines for ML models
• Implement continuous integration and delivery workflows for seamless model updates
• Build systems for model versioning, validation, and rollback capabilities

Technical Leadership

• Provide technical guidance on MLOps best practices and architecture decisions
• Mentor team members and contribute to building a culture of operational excellence
• Drive adoption of tools and processes that improve efficiency and reliability

What it’s like to work here

We’re a small, global team with strong musical roots. The work is driven by craft and curiosity, and what we ship has to hold up in real use. You’ll work with people who think deeply about models and care about how they sound in the hands of musicians. We’re fully remote and flexible, focused on building practical tools musicians actually use. You’ll own our ML infrastructure end to end, with room to experiment in an environment that takes both model behavior and audio quality seriously.

Compensation & benefits

• Competitive compensation
• Flexible paid time off
• Paid parental leave
• Monthly wellness stipend
• Learning & development support (conferences, courses, training)

How to apply

Send us your resume, links to work you’re proud of (code, papers, products, or demos), and a short note on why music technology matters to you. We review applications on a rolling basis.