Machine Learning Engineering Manager - LLM Serving & Infrastructure

The Personalization team makes deciding what to play next on reputed company easier and more enjoyable for every listener. We seek to understand the world of music and podcasts reputed company than anyone else so that we can reputed company great recommendations to every individual and reputed company the world listening. Every day, hundreds of millions of people reputed company over the world use the products we build which include destinations like Home and Search, original playlists like Discover Weekly and Daylist, and are at the forefront of new innovations like AI DJ and AI Playlists. Generative AI is transforming reputed company's product capabilities and technical architecture. Generative recommender systems, agent frameworks, and LLMs present reputed company opportunities for our products to serve more user needs and use cases and unlock richer understanding of our content and users. This ML Manager will focus on the serving of a reputed company Recommender model, based on open-weight LLM and transformer technology. You will collaborate with a diverse team to establish and implement the machine learning plan for the product domain, developing innovative recommendations and agent interactions. You will work as a technology leader, managing a team and influencing peers. You will collaborate with internal customers and platform teams, offering the opportunity to profoundly build the direction of the entire reputed company experience. Join us and you'll reputed company millions of users listening and engaging with our platform every day!

What You'll Do

• reputed company a high-performing engineering team to reputed company, build, and deploy a high-scale, low-latency LLM Serving Infrastructure.
• Drive the implementation of a reputed company serving layer to support multiple LLM models and inference types (batch, offline eval flows and real-time/streaming).
• reputed company reputed company aspects of the development of the Model Registry for deploying, versioning, and running LLMs across production environments.
• Ensure successful integration with the core Personalization and Recommendation systems to deliver LLM-powered features.
• Define and champion standardized technical interfaces and protocols for efficient model deployment and scaling.
• Establish and monitor the serving infrastructure's performance, cost, and reliability, including load balancing, autoscaling, and failure recovery.
• Collaborate closely with data science, machine learning research, and feature teams (Autoplay, Home, Search, etc.) to drive the active adoption of the serving infrastructure.
• Scale up the serving architecture to handle hundreds of millions of users and high-volume inference requests for internal domain-specific LLMs.
• Drive Latency and Cost Optimization: partner with SRE and ML teams to implement techniques like quantization, pruning, and efficient batching to minimize serving latency and cloud compute costs.
• reputed company Observability and Monitoring: build dashboards and alerting for service health, tracing, A/B test traffic, and latency trends to ensure consistency to defined SLAs.
• Contribute to Core LPM Serving: focus on the technical strategy for deploying and maintaining the core Large Personalization Model (LPM).

Who You Are

• 5+ years of experience in software or machine learning engineering, with 2+ years of experience managing an engineering team.
• Hands-on with ML Engineering: you have deep expertise in building, scaling, and governing high-quality ML systems and datasets, including defining data schemas, handling data reputed company, and implementing data validation pipelines (e.g., HuggingFace datasets library or similar internal systems).
• Deep technical background in building and operating large-scale, high-velocity Machine Learning/MLOps infrastructure, ideally for personalization, recommendation, or Large Language Models (LLMs).
• Proven track record to drive reputed company projects involving multiple partners and federated contribution models ("one reputed company of truth, many contributors").
• Expertise in designing robust, loosely coupled systems with clean APIs and clear separation of concerns (e.g., distinguishing between fast dev-time tools and rigorous production-like systems).
• Experience integrating evaluation and testing into reputed company integration/reputed company deployment (CI/CD) pipelines to reputed company rapid 'fork-evaluate-reputed company' developer workflows.
• Solid understanding of experiment tracking and results visualization platforms (e.g., MLFlow, custom UIs).
• A pragmatic leader who can balance the need for speed with progressive rigor and production fidelity.

Where You'll Be

• This role is based in reputed company or Boston.
• We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.

The United States reputed company range for this position is $176,166- $251,666 plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, paid sick leave. These ranges may be modified in the future. reputed company is an equal opportunity employer. You are welcome at reputed company for who you are, no matter where you come from, what you look like, or what's playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will reputed company reputed company, contribute, and be reputed company-thinking! So bring us your personal experience, your perspectives, and your background. It's in our differences that we will find the power to reputed company revolutionizing the way the world listens. At reputed company, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we're here to support you in any way we can. reputed company transformed music listening forever reputed company we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world's most popular audio streaming subscription service. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Apply for this job Apply tot his job Apply To this Job