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Join New York Life's Accident and Health team to underwrite Business Travel Accident and Special Risk policies, manage external relationships, and collaborate internally while resolving client and broker issues.
Our mission on the Advertising Product & Technology team is to build a next generation advertising platform that aligns with our unique value proposition for audio and video. We work to scale the user experience for hundreds of millions of fans and hundreds of thousands of advertisers. This scale brings unique challenges as well as tremendous opportunities for our artists and creators.
We are seeking a Machine Learning Engineer II with expertise in machine learning model development, AI engineering, online experimentation techniques, and large-scale engineering systems. This role will lead strategic initiatives and projects within CareML.
The CareML squad focuses on enabling review for podcast content and ads with respect to brand safety and suitability. By leveraging data and experimentation, we aim to categorize topics existing on both content and ads in various taxonomies that are used to drive large-scale ad serving systems for all of Spotify. We operate on the cutting edge of both machine learning and AI engineering, employing both in-house first party models developed through traditional machine learning and third-party foundation models leveraged from different providers.
We are looking for someone who is motivated by user and business problems as much as they are by technical problems, and who enjoys ambiguity, brainstorming, experimentation, and iteration. You will work in close collaboration with key stakeholders across engineering, product, business, and leadership teams to build the most impactful solutions for our Spotify listeners and business.
What You'll Do
- Design and implement machine learning systems to categories ad and podcast content
- Research and apply best practices for driving automation with respect to human review processes
- Partner with multiple teams to shape and enhance shared systems and pipelines
- Come up with creative ways to apply AI tools to develop innovative solutions
- Collaborate with and backend engineers, data scientists, and product managers to establish baselines, inform product decisions, and develop new technologies
Who You Are
- You have professional experience in applied machine learning
- You are proficient in programming languages such as Python, Java, or Scala
- You have experience with operating in a cloud-native infrastructure
- You have worked with LLMs to deliver solutions through AI engineering
- As a plus, you may have experience with adtech, categorization systems, and evaluation tools / data curation techniques
Where You'll Be
- We offer you the flexibility to work where you work best! For this role, you can be within the Americas region as long as we have a work location.
- This team operates within the Eastern time zone for collaboration.
The United States base range for this position is $138,250.00 - $197,500.00, 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. This range encompasses multiple levels. Leveling is determined during the interview process. Placement in a level depends on relevant work history and interview performance. These ranges may be modified in the future.
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.
Spotify transformed music listening forever when 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.
Spotify New York, New York, USA Office
4 World Trade Center, New York, NY, United States, 10007
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
