机器学习工程经理 - 音乐
Machine Learning Engineering Manager - Music
你将负责
领导、指导并发展一支跨职能的机器学习、数据和后端工程师团队，在给予有经验的成员有意义的自主权的同时，在需要时提供积极的指导和辅导。
在复杂的机器学习系统上提供技术领导力，深入参与建模策略和实现，以挑战假设、评估权衡、识别风险并帮助团队做出决策。
与业务、产品、洞察力及个性化任务的跨职能利益相关者进行代表和倡导，平衡技术问题与业务需求。
赋予工程师自主决定技术决策的能力，但也要在团队需要时提供方向、解决权衡或亲自做出决策。
作为跨职能合作伙伴请求的联系人，过滤重要的更新信息传达给团队，并保护他们的专注时间。
负责健康的交付流程，包括优先级排序、容量管理、运营健康和可靠执行，同时倾向于轻量级的流程，帮助团队快速行动并学习。
保持对工程技艺的熟悉，在适当的时候担任球员兼教练，包括亲自参与技术问题解决和工程工作。
帮助团队在工程流程中有效使用人工智能，并识别AI可以改进我们构建方式和创建的机器学习系统的机遇。
随着团队的发展，招聘和入职工程师，建立团队长期保持韧性所需的能力建设和知识分布。
你将具备
管理工程师的经验，并有开发和管理技术人员的明确记录。
你拥有扎实的机器学习背景，能够可信地参与建模策略、机器学习系统设计以及与资深机器学习从业者的技术讨论。
你可以独立评估机器学习策略和技术权衡，挑战假设，并向技术和非技术的利益相关者清晰地表达技术方向。
你在需要考虑不断变化的产品和业务需求的技术战略环境中感到舒适，并能通过突然的方向转变为你的团队创造清晰度。
你通过给予有经验的工程师自主权并避免不必要的监督来赢得他们的信任，同时保持足够接近他们的工作以有效指导、理解风险并在需要时介入。
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What You'll Do
Lead, coach, and develop a multidisciplinary team of ML, data, and backend engineers, giving experienced ICs meaningful autonomy while providing active mentorship and coaching where needed.
Provide technical leadership on complex ML systems, engaging deeply enough with modeling strategy and implementation to challenge assumptions, assess tradeoffs, identify risks, and help the team make decisions.
Represent and advocate for the team with cross-functional stakeholders across business, product, insights, and the personalization mission, balancing technical concerns with business needs.
Empower engineers to own technical decisions, but recognize when the team needs you to provide direction, resolve a tradeoff, or make the decision yourself.
Be the point of contact for requests from cross-functional partners, filtering the important updates to the team and preserving their heads down time.
Own healthy delivery, including prioritization, capacity management, operational health, and reliable execution, while favoring lightweight processes that help the team move quickly and learn.
Stay close to the engineering craft and act as a player-coach when useful, including contributing hands-on to technical problem solving and engineering work.
Help the team use AI effectively in engineering workflows and identify opportunities for AI to improve both how we build and the ML systems we create.
Hire and onboard engineers as the team evolves, building the capabilities and knowledge distribution needed for the team to remain resilient over time.
Who You Are
Experience managing engineers and a demonstrated track record of developing and managing technical ICs.
You have a solid background in machine learning and can engage credibly in modeling strategy, ML system design, and technical discussions with experienced ML practitioners.
You can independently assess ML strategies and technical tradeoffs, challenge assumptions, and clearly represent a technical direction with both technical and non-technical stakeholders.
You are comfortable operating in an environment where technical strategy must account for evolving product and business needs, and can create clarity for your team through sudden shifts in direction.
You build trust with experienced engineers by giving them autonomy and avoiding unnecessary oversight, while remaining close enough to their work to coach effectively, understand risks, and step in when needed.
You view yourself as your team’s advocate.
You are a thoughtful leader who knows when to facilitate a decision, when to let the team decide, and when to make the decision yourself.
You favor lightweight, purposeful processes over process for its own sake. You can maintain a strong understanding of work, risks, and delivery without creating unnecessary overhead for the team.
You are comfortable making calculated tradeoffs, learning through iteration, and helping teams move quickly while maintaining appropriate technical and operational standards.
You can manage substantial technical, product, and business dependencies with partner teams and build credibility with senior cross-functional stakeholders.
You are comfortable using AI tools and have a point of view on how AI can improve engineering effectiveness and evolve ML-powered products.
You value healthy disagreement, clear ownership, accountability, and an inclusive environment where people can do their best work.
Experience with data engineering and backend is a plus.
Where You'll Be
We offer you the flexibility to work where you work best! For this role, it can be within the North America region in which we have a work location.
This team collaborates across the Eastern time zone
Spotify is an equal opportunity employer. You are welcome at Spotify 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 all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.
At Spotify, 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.