mechanical engineer

mep mechanical engineer

process engineer

ml engineer

Spotify

<div><div><div><div><div><div>Engineering</div></div></div><div><div>
Machine Learning</div></div></div><div><div>
Permanent</div></div><div><div>
New York</div></div><div><div>
The Personalization team at Spotify aims to make content discovery effortless and enjoyable for every listener. By deeply understanding music, podcasts, audiobooks, and videos, we deliver exceptional recommendations that keep millions of people worldwide engaged with our products daily. Our work spans experiences like Home, Search, curated playlists such as Discover Weekly and Daylist, and cutting-edge innovations including AI DJ and AI Playlists.</div></div><div><div><div><br>
</div><div>Home plays a pivotal role in shaping the technical vision and architecture of recommendation systems that power the Spotify Home page. You&rsquo;ll work on foundational components that enable the larger Home experience, user activation, listening habits across content types, and expanding its technology to take advantage of LLMs and other Generative Recommender products. As a Staff Machine Learning Engineer in Home, you&rsquo;ll focus on recommender systems modeling at the intersection of generative recommenders and a foundational understanding of user taste across music and talk content.
</div><div></div><br>
<div>You will define and execute the ML technical strategy for Home, building the next generation of Spotify&rsquo;s recommendation systems, user representations, and supporting technical architecture. Join us and you&rsquo;ll help millions of users discover and connect with the world&rsquo;s audio content every day.</div></div></div></div><div><div><p>
What You'll Do</p><ul><li>
Define and drive the ML technical strategy for Home, focusing on generative recommendation approaches</li><li>
Build models that improve user representations, personalization, and relevance across Spotify&rsquo;s experiences</li><li>
Collaborate with a cross-functional agile team spanning user research, design, data science, product management, and engineering</li><li>
Prototype and productionize new modeling approaches at scale, serving hundreds of millions of users worldwide</li><li>
Lead high-impact projects from ideation through deployment, setting best practices for ML development, testing, evaluation, and experimentation</li><li>
Partner with tech leaders and stakeholders to influence priorities and ensure long-term scalability and impact</li><li>
Stay engaged with the broader ML and Search research community, applying emerging trends to Spotify&rsquo;s challenges</li></ul></div></div><div><div><p>
Who You Are</p><ul><li>
You have a strong background in machine learning and recommender systems, bridging research and user impact</li><li>
You have hands-on experience training and operating transformer models in production, or strong interest in doing so</li><li>
You have production experience developing large-scale ML systems in Java, Scala, Python, or similar languages. Experience with PyTorch or TensorFlow is a strong plus</li><li>
You are comfortable navigating ambiguity and leading high-impact projects from start to finish</li><li>
You&rsquo;re a systems thinker and strong communicator who can align and influence technical and product stakeholders</li><li>
You care deeply about agile processes, data-driven development, and reliability.You&rsquo;re eager to apply emerging ML trends, particularly in LLMs and generative recommenders, to Spotify&rsquo;s challenges</li></ul></div></div><div><div><p>
Where You'll Be</p><ul><li>
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.</li><li>
This team operates within the Eastern Standard time zone for collaboration.</li></ul></div></div><div><div><p>
Learn about life at Spotify</p></div><div><div>
The United States base range for this position is $215,136- $307,337 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.</div></div></div><div><div><p>
Our global benefits</p></div><div></div><div><div>
Extensive learning opportunities, through our dedicated team, GreenHouse.</div></div><div></div><div><div>
Flexible share incentives letting you choose how you share in our success.</div></div><div></div><div><div>
Global parental leave, six months off - for all new parents.</div></div><div></div><div><div>
All The Feels, our employee assistance program and self-care hub.</div></div><div></div><div><div>
Flexible public holidays, swap days off according to your values and beliefs.</div></div></div></div><div></div>

Staff Machine Learning Engineer

Intuit

<div><h2 class="jobSectionHeader"><b>Overview</b></h2><div>
Intuit is looking for an innovative and hands-on <b>Staff AI Scientist</b> to join the Intuit AI team.</div><div></div><div><br>
Come join our collaborative and creative group of AI scientists and machine learning engineers and build models that directly affect hundreds of thousands of our customers. In this role you will be building and deploying machine learning models using both analytical algorithms and deep learning approaches.</div><p><b><br>
Responsibilities</b></p><ul><li>
Practices leadership and communication skills to influence teams and to evangelize AI science across the organization</li><li>
Collaborates with stakeholders to define success criteria and align model metrics with business goals. Works side-by-side with product managers, software engineers, and designers in designing experiments and minimum viable products</li><li>
Leads technical work of a scrum team: initiating and designing model solutions, driving end-to-end architecture designs of the team&rsquo;s work, and holding the team accountable for high quality code, git, design, costs and implementation standards</li><li>
Performs hands-on data analysis and modeling with large data sets, including discovering data sources, getting data access, cleaning up data, and making them &ldquo;model-ready&rdquo;. You need to be willing and able to do your own ETL and design/build featurization.</li><li>
Applies data mining, NLP, and machine learning (such as supervised/unsupervised, Causal-ML, Online Learning, Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and datasets.</li><li>
Runs A/B tests to draw conclusions on the impact of your team&rsquo;s work and communicates results to peers and leaders</li><li>
Communicates with partners to ensure successful delivery and integration of DS solutions.</li><li>
Proactively researches, explores, and enables new ML technologies. Keeps up with the new developments in academia and industry and considers possible extensions to solve Intuit customer problems.<br>
<i>Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing pay equity for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.</i></li></ul><p><b><br>
Qualifications</b></p><ul><li>
4+ years of industry experience with AI science</li><li>
BS, MS or PhD in Statistics, Mathematics, Computer Science, Economics, Operations Research, or equivalent</li><li>
4+ years of hands-on expertise in ML paradigms such as Causal-ML, supervised/unsupervised, Online, Bayesian, Reinforcement or Deep Learning.</li><li>
Proficient in multiple optimization paradigms such as combinatorial optimization, gradient methods, or Bayesian optimization.</li><li>
Proficient in NLP techniques, Explainable AI, and ML frameworks.</li><li>
Expertise in modern advanced analytical tools and programming languages such as Python, Scala, Java and/or R.</li><li>
Efficient in SQL, Hive, SparkSQL, etc.</li><li>
Comfortable working in a Linux environment</li><li>
Experience with building end-to-end reusable pipelines from data acquisition to model output delivery</li><li>
Quick learner, adaptable, with the ability to work independently in a fast-paced environment</li><li>
Strong oral and written communication skills. Ability to conduct meetings and make professional presentations, and to explain complex concepts and technical material to non-technical users</li></ul><p><br>
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit&reg;: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is:
<br>
New York<i>: $201,500 - $273,000</i></p></div><p></p>

Staff AI Scientist

<div><div><div><div><div><div>Engineering</div></div></div><div><div>
Machine Learning</div></div></div><div><div>
Permanent</div></div><div><div>
New York</div></div><div><div>
Our mission on the Advertising Product &amp; 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.</div></div><div><div><div><br>
</div><div>We are seeking a Senior Machine Learning Engineer to join the Ad Engagement squad. Ad Engagement focuses on using machine learning to accurately predict how Spotify listeners will react to ads, helping advertisers minimize their costs while delivering a more relevant and enjoyable ad experience for listeners. Our core innovations include Multi-Task Learning models (MTL), and we are expanding into scalable sequence modeling with complex transformer architectures. Recently, we presented a paper about this in KDD Toronto and you can check out the latest details in the blog post here.</div><div><br>
</div><div>We are also seeking a Senior Machine Learning Engineer to join the Supply Personalization squad. Supply Personalization focuses on optimizing the volume, timing, and types of ad loads a user receives. By leveraging data, machine learning, causal inference, and large scale online experimentation, we aim to uncover and learn the most effective strategies for enhancing user experiences and driving business outcomes.</div><div><br>
</div><div>We are looking for someone with strong expertise in data analysis, online experimentation techniques, and large-scale ML and engineering systems; someone who is motivated by user and business problems as much as they are by technical problems, and who thrives under ambiguity, experimentation, and iteration. You will work directly on an array of product features that drive the optimal user experience for our ads. You will collaborate with our cross-functional teams to ideate, develop, and own complex technical solutions on our ad services technology platforms. As someone who shares our passion for building innovative ad experiences, you'll have a direct impact on how the world uses Spotify.</div></div></div></div><div><div><p>
What You'll Do</p><ul><li>
Design and implement machine learning systems for ad performance optimization.
</li><li>Research and apply ML optimization strategies to balance multiple objectives effectively.</li><li>
Work on a paradigm shift modeling work for Ads that involves working on Sequence Transformer model for User-Ad Interaction, that works along a MTL model</li><li>
Analyze data and use machine learning techniques to understand user behavior and improve ad experiences.</li><li>
Collaborate with backend engineers, data scientists, data engineers, and product managers to establish baselines, inform product decisions, and develop new technologies.</li></ul></div></div><div><div><p>
Who You Are</p><ul><li>
You have professional experience in applied machine learning.</li><li>
You have strong technical expertise in software engineering, data analysis, and machine learning.</li><li>
You are proficient in programming languages such as Python, Java, or Scala.</li><li>
Experienced in Tensorflow or PyTorch and working with various aspects of the ML lifecycle</li><li>
You have expertise in developing data pipelines using tools like Apache Beam or Spark.</li><li>
As a plus, you may have experience with any of the following - LLMs, Ray, Adtech, or Recommender Systems.</li></ul></div></div><div><div><p>
Where You'll Be</p><ul><li>
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.</li><li>
This team operates within the U.S. Eastern time zone for collaboration.</li></ul></div></div><div><div><p>
Learn about life at Spotify</p></div><div><div>
The United States base range for this position is $176,166.00 - $251,666.00, 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.</div><div></div><div><br>
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&rsquo;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&rsquo;s in our differences that we will find the power to keep revolutionizing the way the world listens.</div><div></div><div><br>
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&rsquo;re here to support you in any way we can.</div><div></div><div><br>
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&rsquo;s most popular audio streaming subscription service.</div></div></div><div></div><div><div><p><br>
Our global benefits</p></div><div></div><div><div>
Extensive learning opportunities, through our dedicated team, GreenHouse.</div></div><div></div><div><div>
Flexible share incentives letting you choose how you share in our success.</div></div><div></div><div><div>
Global parental leave, six months off - for all new parents.</div></div><div></div><div><div>
All The Feels, our employee assistance program and self-care hub.</div></div><div></div><div><div>
Flexible public holidays, swap days off according to your values and beliefs.</div></div></div></div><div></div>

Senior Machine Learning Engineer, Ads R&D

Amazon.com

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
We are looking for a passionate Applied Scientist to help pioneer the next generation of agentic AI applications for Amazon advertisers. In this role, you will design agentic architectures, develop tools and datasets, and contribute to building systems that can reason, plan, and act autonomously across complex advertiser workflows. You will work at the forefront of applied AI, developing methods for fine-tuning, reinforcement learning, and preference optimization, while helping create evaluation frameworks that ensure safety, reliability, and trust at scale.
<br>
<br>
You will work backwards from the needs of advertisers&mdash;delivering customer-facing products that directly help them create, optimize, and grow their campaigns. Beyond building models, you will advance the agent ecosystem by experimenting with and applying core primitives such as tool orchestration, multi-step reasoning, and adaptive preference-driven behavior. This role requires working independently on ambiguous technical problems, collaborating closely with scientists, engineers, and product managers to bring innovative solutions into production.<br>
<br>
Key job responsibilities<br>
<ul><li>Design and build agents to guide advertisers in conversational and non-conversational experience.</li><li>Design and implement advanced model and agent optimization techniques, including supervised fine-tuning, instruction tuning and preference optimization (e.g., DPO/IPO).</li><li>Curate datasets and tools for MCP.
</li><li>Build evaluation pipelines for agent workflows, including automated benchmarks, multi-step reasoning tests, and safety guardrails.</li><li>Develop agentic architectures (e.g., CoT, ToT, ReAct) that integrate planning, tool use, and long-horizon reasoning.</li><li>Prototype and iterate on multi-agent orchestration frameworks and workflows.</li><li>Collaborate with peers across engineering and product to bring scientific innovations into production.</li><li>Stay current with the latest research in LLMs, RL, and agent-based AI, and translate findings into practical applications.</li></ul><br>
About the team<br>
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through the latest generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights.<br>
<br>
We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising.<br>
<br>
The Advertiser Guidance team within Sponsored Products and Brands is focused on guiding and supporting 1.6MM advertisers to meet their advertising needs of creating and managing ad campaigns. At this scale, the complexity of diverse advertiser goals, campaign types, and market dynamics creates both a massive technical challenge and a transformative opportunity: even small improvements in guidance systems can have outsized impact on advertiser success and Amazon&rsquo;s retail ecosystem.<br>
<br>
Our vision is to build a highly personalized, context-aware agentic advertiser guidance system that leverages LLMs together with tools such as auction simulations, ML models, and optimization algorithms. This agentic framework, will operate across both chat and non-chat experiences in the ad console, scaling to natural language queries as well as proactively delivering guidance based on deep understanding of the advertiser. To execute this vision, we collaborate closely with stakeholders across Ad Console, Sales, and Marketing to identify opportunities&mdash;from high-level product guidance down to granular keyword recommendations&mdash;and deliver them through a tailored, personalized experience. Our work is grounded in state-of-the-art agent architectures, tool integration, reasoning frameworks, and model customization approaches (including tuning, MCP, and preference optimization), ensuring our systems are both scalable and adaptive.</div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience</li><li>3+ years of building models for business application experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience in designing experiments and statistical analysis of results</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience in professional software development</li><li>Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.<br>
<br>
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.<br>
<br>
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.</div>

Applied Scientist

Software Engineer, Machine Learning

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
About Sponsored Products and Brands<br>
<br>
The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising.<br>
<br>
Key job responsibilities<br>
As a Software Development Engineer in Machine Learning, you will:
<br>
<ul><li>Enhance the scalability, automation, and efficiency of large-scale training and real-time inference systems.</li><li>Pioneer the development of LLM inference infrastructure to support next-generation GenAI workloads at Amazon Ads scale.</li><li>Work closely with applied scientists to optimize the performance of machine-learning models and infrastructure, and implement end-to-end solutions.</li></ul><br>
About the team<br>
SPB Ad Response Prediction team is your choice, if you want to join a highly motivated, collaborative, and fun-loving team with a strong entrepreneurial spirit and bias for action. We are looking for a talented Software Engineer with a strong background in machine learning engineering to join our team and help us grow the business. In this role, you will partner with a team of engineers and scientists to build advanced machine learning models and infrastructure, from training to inference, including emerging LLM-based systems, that deliver highly relevant ads to shoppers across all Amazon platforms and surfaces worldwide.</div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>5+ years of non-internship professional software development experience</li><li>5+ years of programming with at least one software programming language experience</li><li>5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience</li><li>Experience as a mentor, tech lead or leading an engineering team</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience</li><li>Bachelor's degree in computer science or equivalent</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.<br>
<br>
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.<br>
<br>
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $151,300/year in our lowest geographic market up to $261,500/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.</div>

Sr. Software Dev Engineer, Sponsored Products and Brands Ads Response Prediction

<div><div><div><div><div><div>Engineering</div></div></div><div><div>
Machine Learning</div></div></div><div><div>
Permanent</div></div><div><div>
New York</div></div><div><div>
The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Discover Weekly to AI DJ, we&rsquo;re behind some of Spotify&rsquo;s most-loved features. We built them by understanding the world of music, podcasts, and listeners better than anyone else. Join us and you&rsquo;ll keep millions of users listening by making great recommendations to each and every one of them.</div></div><div><div><div><br>
</div><div>The Next Generation Sessions (NextGen) product area within Personalization is evolving listening beyond playlists, inventing new personalized listening (and watching!) sessions such as AI DJ, AI Playlist, Blend, Podcast Discovery Feed, and Music Discovery Feed. NextGen is a team of about 100 engineers, scientists, product managers, and music and voice domain experts working remotely and in offices in New York, Boston, London, and Stockholm.</div><div><br>
</div><div>This ML Engineering Manager role will provide technical leadership to a newly formed squad of ~12 engineers focusing on exciting new AI-driven music session experiences. In collaboration with a cross-functional and cross-team leadership group, you will drive expansion of NextGen's AI experiences in music, leveraging the success of AI DJ and AI Playlist, advancing and spearheading the development of entirely new music recommendations experiences and capabilities.</div></div></div></div><div><div><p>
What You'll Do</p><ul><li>
Lead a talented team of ML, backend, and data engineers to build and launch innovative AI-driven personalized music experiences</li><li>
Debate and align technical strategies with senior engineering leaders and partner teams, translate these strategies clearly back to your squad, and actively guide architectural vision and day-to-day ML modeling and coding decisions</li><li>
Bring external experience in generative AI and agent frameworks to enhance Spotify's personalized music sessions</li><li>
Navigate ambiguity, driving innovation through rapid prototyping and iterative development in cross-functional teams</li><li>
Champion AI-assisted coding practices, continually expanding the team's technical capabilities</li><li>
Foster strong research partnerships to scale innovative solutions from experimentation to production</li><li>
Develop and grow your team's talent through hiring, coaching, mentoring, and fostering a collaborative, adaptive culture</li></ul></div></div><div><div><p>
Who You Are</p><ul><li>
Experienced leading delivery of consumer-facing ML products at scale</li><li>
Energized by rapid change, ambiguity, and opportunity, with a proven track record transforming innovative ideas into impactful products</li><li>
Skilled with current generative AI and agent technologies</li><li>
Actively using AI-assisted coding and product development tools to prototype new products</li><li>
Expert in modern ML theory, practices, and their practical implementation</li><li>
Comfortable providing detailed technical direction and resolving complex engineering challenges</li><li>
Collaborative and influential, thriving in strategic discussions with senior engineers and managers</li><li>
Focused on user outcomes, rigorously grounding decisions in user data and insights</li><li>
Experienced in nurturing technical talent, committed to growing engineers' skills in technology and leadership</li></ul></div></div><div><div><p>
Where You'll Be</p><ul><li>
We offer you the flexibility to work where you work best! For this role, you can be within the EST time zone as long as we have a work location. The squad is based in New York City.</li><li>
This team operates within the Eastern Standard time zone for collaboration.</li></ul></div></div><div><div><p>
Learn about life at Spotify</p></div><div><div>
The United States base 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.</div><div></div><div><br>
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&rsquo;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&rsquo;s in our differences that we will find the power to keep revolutionizing the way the world listens.</div><div></div><div><br>
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&rsquo;re here to support you in any way we can.</div><div></div><div><br>
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&rsquo;s most popular audio streaming subscription service.</div></div></div><div><div><p>
Our global benefits</p></div><div></div><div><div>
Extensive learning opportunities, through our dedicated team, GreenHouse.</div></div><div></div><div><div>
Flexible share incentives letting you choose how you share in our success.</div></div><div></div><div><div>
Global parental leave, six months off - for all new parents.</div></div><div></div><div><div>
All The Feels, our employee assistance program and self-care hub.</div></div><div></div><div><div>
Flexible public holidays, swap days off according to your values and beliefs.</div></div></div></div><div></div>

Machine Learning Engineering Manager, Personalization

Explore 79+ Ml engineer in New York this November. Find roles across top companies and apply now to boost your career.