The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them. Samba sits at the heart of Spotify’s personalization engine, powering experiences like autoplay, radio, and personalized mixes. We work on complex sequencing and optimization problems—balancing what users love with how Spotify supports creators and the business. Our team blends machine learning, backend engineering, and data expertise, and collaborates across North America and Europe to deliver impactful, real-time personalization at scale. What You'll Do - Design and build machine learning systems that optimize ranking and sequencing across personalized surfaces - Develop multi-objective optimization strategies that balance user satisfaction with business outcomes - Collaborate closely with cross-functional partners including product, data science, and engineering teams to align on goals, share context, and deliver impactful solutions - Work across ML, backend, and data layers to bring models into production - Contribute to scalable infrastructure supporting high-volume user interactions - Run experiments and use insights to continuously improve performance - Help shape technical direction and raise the bar for engineering excellence within the team Who You Are - You have 5+ years of experience in machine learning, data, or backend engineering - You are experienced with production-grade systems and scalable architectures - You have worked on recommendation systems, ranking, or optimization problems - You bring a T-shaped skillset across ML, data, and backend domains - You are comfortable navigating ambiguity and solving complex problems - You care about user experience and measurable impact - You enjoy collaborating across disciplines and geographies Where You'll Be - We offer you the flexibility to work where you work best! For this role, you can be within the North America region as long as we have a work location. - This team operates within the Eastern Standard time zone for collaboration. The United States base range for this position is $148,901- $212,716 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. 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.

• Work embedded with ML scientists to co-develop and refine model training and evaluation workflows • Translate experimental research code into maintainable, well-structured, and reusable systems • Build and expand benchmarking systems for running models on structural and affinity datasets, computing metrics, and supporting reproducible evaluation • Enable rapid iteration by developing tooling and interfaces that expose new capabilities to researchers • Contribute to the ongoing development and productization of NeuralPLexer • Collaborate with platform and infrastructure engineers on scaling workflows where needed, without owning core infrastructure • Perform code reviews and actively mentor best practices in software engineering across the team • Improve reliability, clarity, and reproducibility of ML workflows and supporting systems • Communicate technical work effectively across a cross-functional research and engineering team

Description Our Mapping organization is building national-scale, next-generation mapping systems that move beyond static HD maps toward automated, ML-driven map reconstruction pipelines powered by onboard sensor data. These systems form a critical foundation for localization, perception, simulation, and autonomy at scale. The Role We are looking for a Staff Machine Learning Engineer to serve as a technical leader for automated map reconstruction within our Mapping Engineering team. In this role, you will architect and deliver end-to-end ML and computer vision pipelines that reconstruct, validate, and maintain map primitives (e.g., lanes, boundaries, traffic controls, signs) from large-scale sensor data. Your work will directly power next-generation maps that operate reliably across national deployments and evolving road conditions. This is a hands-on technical leadership role. You will operate with high autonomy, define technical strategy in ambiguous problem spaces, and lead cross-functional efforts spanning Mapping, Perception, Localization, Simulation, and Infrastructure. You will also mentor senior engineers and help raise the ML and CV bar across the organization. What You'll Do (Responsibilities) - Architect and lead ML-driven map reconstruction systems that operate at national scale using multi-modal sensor data (camera, lidar, radar, vehicle signals). - Design and implement end-to-end pipelines for offline map reconstruction, including data mining, labeling strategies, model training, evaluation, and production deployment. - Define technical strategy and system architecture for next-generation mapping capabilities, balancing ML innovation with robustness, safety, and operational scalability. - Lead the development and adoption of state-of-the-art computer vision and ML techniques (e.g., detection, segmentation, 3D reconstruction, BEV representations) applied to mapping problems. - Own cross-functional technical initiatives, working closely with Perception, Localization, Simulation, and Platform teams to define interfaces, data contracts, and integration points. - Drive technical excellence through design reviews, mentorship, and technical guidance for senior and staff-level engineers across teams. - Diagnose and resolve system-level issues across data pipelines, ML models, and production workflows. - Serve as a Subject Matter Expert (SME) for ML-based mapping and reconstruction within Mapping and across the AV organization. - Contribute to technical roadmaps, hiring, and capability building for ML and CV expertise within the Mapping org. Minimum Qualifications (Must-Have) - 5+ years of experience building and deploying machine learning or computer vision systems in production environments. - Strong foundation in computer vision, machine learning, or robotics, with hands-on experience designing and training ML models. - Proficiency in Python for ML development; familiarity with C++ or other systems languages is a plus. - Experience building large-scale data pipelines for ML, including dataset curation, labeling workflows, training, and evaluation. - Proven ability to lead complex, cross-functional technical initiatives with high autonomy and influence. - BS, MS, or PhD in Computer Science, Electrical Engineering, Robotics, or a related technical field, or equivalent industry experience. - Strong systems thinking - ability to reason about end-to-end ML systems, not just individual models. Preferred Qualifications (Nice-to-Have) - Experience with mapping, localization, perception, or robotics systems, particularly in autonomous driving or mobile robotics. - Hands-on experience with 3D perception, BEV representations, or multi-view geometry. - Familiarity with AV sensor data (camera, lidar, radar) and real-world data challenges (noise, drift, long-tail scenarios). - Experience deploying ML models into production pipelines with monitoring, validation, and iteration loops. - Exposure to simulation-based validation, synthetic data, or map change detection workflows. - Experience mentoring senior engineers or acting as a technical lead across multiple teams. Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York, Colorado, California, or Washington. - The salary range for this role: is $185,100 to $335,300. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position. - Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance. - Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more. Company Vehicle: Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate. Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies. #GM-AV-1 This role is based remotely, but if the selected candidate lives within a specific mile radius of a GM hub, they will be expected to report to the location three times a week {or other frequency dictated by your manager}. This job may be eligible for relocation benefits. About GM Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all. Why Join Us We believe we all must make a choice every day - individually and collectively - to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team. Total Rewards | Benefits Overview From day one, we're looking out for your well-being-at work and at home-so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources. Non-Discrimination and Equal Employment Opportunities (U.S.) General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers. All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws. We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire. Accommodations General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us [email protected] or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.

• Design and implement machine learning systems for ad performance optimization. • Research and apply ML optimization strategies to balance multiple objectives effectively. • Analyze data and use machine learning techniques to understand user behavior and improve ad experiences. • Collaborate with backend engineers, data scientists, data engineers, and product managers to establish baselines, inform product decisions, and develop new technologies.