About the Role
You will lead the development of machine learning solutions that power personalization features, working closely with product and research teams to translate insights into impactful user experiences.
Responsibilities
- Design and implement scalable machine learning models for recommendation systems
- Collaborate with cross-functional teams to integrate models into production environments
- Optimize algorithms for performance, accuracy, and efficiency
- Analyze large-scale user behavior data to inform model development
- Drive end-to-end deployment of machine learning pipelines
- Conduct experiments to evaluate model effectiveness
- Improve personalization systems using real-time data signals
- Mentor engineers and contribute to technical direction
- Stay current with advancements in ML and apply relevant techniques
- Ensure models align with user privacy and ethical standards
- Work closely with data scientists to refine feature engineering
- Develop evaluation frameworks for personalization metrics
- Troubleshoot and resolve issues in live model serving systems
- Contribute to architectural decisions for data infrastructure
- Support A/B testing initiatives for personalization features
- Translate business requirements into technical solutions
- Enhance model interpretability and monitoring tools
- Participate in code and design reviews
- Scale systems to handle global user traffic
- Improve latency and reliability of inference pipelines
- Use feedback loops to refine model performance
- Collaborate on dataset creation and labeling strategies
- Integrate third-party data sources where applicable
- Document technical designs and system behavior
- Advocate for best practices in ML engineering
Compensation
Competitive salary and equity package, commensurate with experience
Work Arrangement
Hybrid work model with flexibility based on team and location
Team
Part of a research-driven team focused on advancing personalization through machine learning innovation
About the Team
Magenta is a research and development team exploring the intersection of machine learning and music. The group focuses on building novel tools and systems that enhance how users discover and interact with audio content through personalization technologies.
What You'll Do
- Lead the design and implementation of machine learning models that power personalized experiences
- Work on systems that recommend music, podcasts, and playlists based on user preferences
- Collaborate with researchers to prototype and scale new ideas
Visa sponsorship available for qualified candidates
