Machine Learning Engineering Manager Recommendations jobs in San Francisco – Browse 8,342 openings on RoboApply Jobs

Machine Learning Engineering Manager Recommendations jobs in San Francisco

Open roles matching “Machine Learning Engineering Manager Recommendations” with location signals for San Francisco. 8,342 active listings on RoboApply Jobs.

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companySuno logo
Full-time|On-site|San Francisco

About SunoSuno is revolutionizing the music industry by harnessing the power of advanced AI technology to inspire creativity. Our innovative platform, which includes the groundbreaking Suno Studio, provides an exceptional generative audio workstation designed for everyone—from casual singers to aspiring songwriters and seasoned musicians. Suno is dedicated to empowering a diverse global community to create, share, and explore music, celebrating the joy of musical expression for all.About the RoleWe are seeking a visionary leader to spearhead our recommendations team at Suno. In this pivotal role, you will be at the forefront of developing our music discovery and recommendation systems, shaping how millions of users engage with music on our platform. Your expertise will drive the evolution of our systems while fostering a collaborative and innovative team environment.This position is ideal for an individual with extensive experience in scaling recommendation systems and a passion for crafting a superior user experience. If you are excited to apply your skills in a dynamic setting and lead a talented team, we want to hear from you!Discover more about this role at Suno!What You'll DoDefine and execute Suno's vision and strategy for recommendations, setting the technical direction for the team.Collaborate with leaders across product, engineering, and research to ensure our recommendations evolve in alignment with platform growth.Lead the design and development of a comprehensive recommendation system, from initial prototyping to large-scale deployment.Recruit, mentor, and expand a high-performing recommendations team.What You'll NeedA minimum of 5 years of experience in building large-scale recommendation systems, with at least 2 years in a leadership role overseeing development.Profound technical knowledge of cutting-edge technologies and methodologies in recommendation systems, along with a pragmatic approach to implementation.Exceptional collaborative skills with a proven ability to influence cross-functional teams.A genuine passion for Suno's mission and a keen interest in shaping the future of music discovery.Bachelor’s degree or equivalent experience.Additional Notes: Candidates must be eligible to work in the United States.This role requires onsite presence in San Francisco.

Jan 6, 2026
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company
Full-time|On-site|San Francisco, CA

About Quizlet:At Quizlet, our vision is to empower every learner to achieve their educational goals in the most effective and enjoyable manner. As a thriving $1B+ educational platform, we serve two-thirds of U.S. high school students and half of college students, facilitating over 1 billion learning interactions weekly.By integrating cognitive science with advanced machine learning techniques, we tailor and enhance the learning experience for students, professionals, and lifelong learners alike. Our enthusiasm lies in the potential to support more learners through diverse methodologies and tools.Let's Shape the Future of Learning TogetherJoin us in designing and implementing AI-driven learning solutions that scale globally, unlocking the potential of learners everywhere.About the Team:The Personalization & Recommendations team is dedicated to crafting customized learning experiences that enable millions of learners to study more effectively. We are seeking Machine Learning Engineers across Senior to Staff levels (including Sr. Staff) to join our innovative team.You will leverage your expertise in modern recommender systems—encompassing deep learning-based retrieval, embeddings, and multi-stage ranking—to enhance Quizlet's personalization capabilities. Collaborating at the nexus of machine learning, product development, and scalable systems, you will ensure our recommendations are efficient, ethical, and aligned with learner outcomes, privacy, and fairness.This is an onsite position, requiring team members to work in the office at least three days a week: Monday, Wednesday, and Thursday, as well as additional days as needed. We believe this in-office collaboration fosters efficiency, enhances teamwork, and promotes both personal and organizational growth.

Apr 9, 2026
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companyKrea logo
Full-time|On-site|San Francisco

About KreaKrea is at the forefront of developing advanced AI creative tools designed to enhance and empower human creativity. Our mission is to create intuitive and controllable AI solutions that allow creatives to express themselves across various formats including text, images, video, sound, and 3D.About the PositionWe are seeking a talented Machine Learning Engineer to lead the design and implementation of Krea’s personalization and recommendation systems from the ground up. You will take full ownership of how we comprehend user preferences, curate engaging content, and customize generative models to reflect individual aesthetics.This role sits at the exciting intersection of recommendation systems, representation learning, and generative imaging and video technologies.Your ResponsibilitiesLead the architecture and development of Krea’s personalization and recommendation framework, overseeing the technical direction from inception to deployment.Craft algorithms that effectively model user preferences and tastes, enabling our systems to adapt to individual styles and aesthetics.Develop high-quality, curated feeds that strike a balance between exploration, personalization, and aesthetic coherence.Collaborate closely with our model and research teams to co-create personalization mechanisms that shape how our generative models learn, adapt, and express creative styles.Contribute to research in personalized image generation, with a focus on style, taste, and subjective quality.Work in tandem with product, design, and research teams to define what “good personalization” means in a creative context.Take systems from initial research and prototyping stages through to production, ongoing iteration, and enhancement.

Dec 17, 2025
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companyPhilo logo
Full-time|Remote|San Francisco, CA or remote within the U.S.

At Philo, we are a dedicated team of technology and product enthusiasts committed to reshaping the television landscape. We blend cutting-edge technology with the captivating medium of television to create the ultimate viewing experience. Our mission is to enhance streaming capabilities through innovative cloud delivery and sophisticated machine learning algorithms that personalize content discovery. As a Senior Machine Learning Engineer specializing in Recommendation Systems, you will be at the forefront of our content personalization initiatives, significantly enhancing user engagement and satisfaction. Your expertise will help ensure that every time users open the Philo app, they find something they want to watch. In this pivotal role, you will spearhead the development of advanced algorithms and large-scale systems that drive Philo's recommendation engine. Collaborating closely with data science, product, infrastructure, and backend engineering teams, you will tackle complex machine learning challenges and develop innovative, data-driven solutions that enhance content discovery and foster user retention.

Mar 18, 2026
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company
Full-time|On-site|San Francisco

Join our dynamic team at Liquid AI as a Member of Technical Staff where you will leverage your expertise in applied machine learning and recommendation systems to drive innovative solutions. You will collaborate with a talented group of professionals in a fast-paced environment, contributing to the development of advanced algorithms that enhance user experience and operational efficiency.

Mar 30, 2026
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companyPinterest, Inc. logo
Internship|On-site|San Francisco, CA, US; Palo Alto, CA, US; Seattle, WA, US; New York, NY, US

Pinterest is looking for a PhD Fall Machine Learning Intern with a focus on visual, multimodal, and recommender systems. This internship centers on supporting advanced machine learning projects alongside skilled engineers and researchers. Role overview The position involves contributing to ongoing research and development in machine learning. Interns will have the chance to work on projects that explore visual understanding and recommendation technologies, learning from experienced team members throughout the process. Collaboration Expect to work closely with engineers and researchers who specialize in machine learning. The environment encourages sharing ideas and building solutions that impact Pinterest’s products. Locations San Francisco, CA, US Palo Alto, CA, US Seattle, WA, US New York, NY, US

Apr 20, 2026
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companyLyft logo
Full-time|$162.8K/yr - $203.5K/yr|On-site|San Francisco, CA

At Lyft, our mission is to connect and serve communities by fostering an inclusive work environment where every team member feels valued and empowered to excel.With over half a billion rides completed, Lyft is tackling complex challenges in a fast-evolving landscape filled with extensive data and innovative solutions across various domains including Marketplace, Mapping, Fraud Prevention, Trust & Safety, and Growth. As we redefine transportation with our next-generation platform, we utilize advanced machine learning techniques that process peta-byte scale data to create low-cost, ultra-immersive transportation solutions that enhance lives. Our dedicated Machine Learning Engineers are at the forefront of these efforts, crafting solutions that significantly influence our core business operations.If you are a critical thinker with a robust background in machine learning workflows, passionate about leveraging data to solve business challenges, and thrive in a dynamic, collaborative setting, we want to hear from you!As a Senior Machine Learning Engineer, you will design and implement algorithms that drive the core services and influential products of our platform. The range of challenges we tackle is remarkably diverse, spanning transportation, economics, forecasting, mapping, safety, personalization, and adaptive control. We are eager to welcome motivated experts in these fields who are excited about developing reliable ML systems and solving problems through data in an innovative and fast-paced environment.

Feb 20, 2026
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companyOrchard logo
Full-time|On-site|San Francisco

Join Orchard as a Machine Learning Engineer and play a pivotal role in transforming data into actionable insights. In this dynamic position, you will leverage your expertise in machine learning algorithms and data analysis to develop innovative solutions that enhance our products and services.We are looking for a proactive team player who thrives in a fast-paced environment and possesses strong problem-solving skills. You will collaborate with cross-functional teams, engage with large datasets, and contribute to the design and implementation of machine learning models.

Mar 14, 2026
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companyPinterest, Inc. logo
Full-time|Remote|San Francisco, CA, US; Remote, US

Join Pinterest as a Manager II in Machine Learning Engineering and lead a team of talented engineers and data scientists in developing innovative machine learning solutions. You will play a crucial role in driving the technical direction of our projects, ensuring the delivery of high-quality models and algorithms that enhance user experience and engagement. You will collaborate with cross-functional teams and stakeholders to understand business needs and translate them into technical requirements.

Apr 9, 2026
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companyHandshake logo
Full-time|On-site|San Francisco, CA

Join Handshake as a Machine Learning Engineer I, where you will have the opportunity to work on cutting-edge machine learning projects that drive our innovative solutions. Collaborate with a talented team to develop algorithms and models that enhance our product offerings and improve user experiences.

Apr 6, 2026
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companyHive logo
Full-time|On-site|San Francisco

Join Our Innovative Team at HiveHive is at the forefront of cloud-based AI solutions, revolutionizing how organizations understand, search for, and generate content. Trusted by many of the world's largest and most groundbreaking companies, we empower developers with premier pre-trained AI models that handle billions of API requests monthly. Our turnkey software applications leverage proprietary AI models and datasets, driving transformative advancements in content moderation, brand protection, sponsorship measurement, and context-based ad targeting.With over $120M in funding from prominent investors like General Catalyst, 8VC, Glynn Capital, Bain & Company, and Visa Ventures, Hive is rapidly expanding. Our dynamic team of over 250 employees operates from our San Francisco, Seattle, and Delhi offices. If you are passionate about shaping the future of AI, we invite you to explore opportunities with us!About the Machine Learning Engineer RoleAs we strive to achieve our ambitious vision, we seek exceptional machine learning engineers to join our team. We are looking for enthusiastic developers who are eager to remain at the cutting edge of deep learning technology, designing and deploying state-of-the-art neural network models into production. Our ideal candidates thrive in working with large-scale datasets and demonstrate a keen interest in mastering new technologies across the machine learning spectrum. We value individuals who are proactive and take ownership of their projects, contributing innovative ideas and practical implementations. Experience in building machine learning applications from the ground up and designing scalable, maintainable data pipelines is essential.

Jan 15, 2021
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companyBoomtrain logo
Full-time|On-site|San Francisco

Join our dynamic Personalization team at Boomtrain as a Machine Learning Engineer. We are in search of a skilled engineer who will play a pivotal role in developing and enhancing our recommendation systems that cater to a variety of customers.In this role, you will collaborate with a talented team dedicated to designing and implementing innovative models and systems that deliver personalized recommendations. You will have the opportunity to work on complex engineering challenges and contribute to generating hundreds of millions of recommendations daily.This position offers a unique chance to engage in end-to-end project work and make a significant impact on our personalization initiatives.Key Responsibilities:Research and propose advanced recommendation and optimization models to enhance our personalization systems.Develop and maintain offline model generation pipelines.Design and maintain online recommendation serving systems.

Jul 21, 2016
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companyFaire logo
Internship|$75K/yr - $75K/yr|On-site|San Francisco, CA

About Faire Faire is an online wholesale marketplace focused on supporting independent retailers. By connecting small businesses with products from around the world, Faire aims to help local shops compete with major players like Walmart and Amazon. The company uses technology, data analytics, and machine learning to provide insights and tools that level the playing field for entrepreneurs everywhere. Faire’s work strengthens local economies by enabling independent businesses to thrive. The team values resourcefulness, intelligence, and a commitment to community. Those who believe in supporting local businesses will find a shared purpose here. Role Overview: Data Science Intern – Personalization & Recommender Systems This internship focuses on building and improving machine learning systems that power search, personalization, and recommendations for Faire’s marketplace. Interns will join a team dedicated to developing algorithms that help local retailers discover relevant products and compete with larger competitors. The team welcomes Master’s and PhD students with a background in recommender systems, personalization, or applied machine learning. Who We’re Looking For Strong interest in recommender systems and personalization Experience applying modern machine learning techniques to ranking or representation learning PhD candidates: a record of publications or submissions to top conferences (such as KDD, RecSys, ICML, NeurIPS, WWW, SIGIR) Master’s candidates: meaningful research projects, internships, or open-source contributions in related areas What You’ll Work On Design and build advanced recommender systems for product ranking and discovery Develop methods for user and item representation learning Collaborate with machine learning engineers to move research solutions into production Tackle personalization challenges that impact millions of recommendations each day Location San Francisco, CA

Apr 18, 2026
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companyPulse logo
Full-time|On-site|San Francisco

OverviewPulse is revolutionizing data infrastructure by addressing the critical challenge of extracting accurate, structured information from complex documents on a large scale. Our innovative approach to document understanding integrates intelligent schema mapping with advanced extraction models, outperforming traditional OCR and parsing methods.As a dynamic and rapidly growing team of engineers based in San Francisco, we empower Fortune 100 companies, Y Combinator startups, public investment firms, and growth-oriented businesses. With the backing of top-tier investors, we are on an exciting growth trajectory.What sets our technology apart is our cutting-edge multi-stage architecture:Layout comprehension with specialized component detection modelsLow-latency OCR models designed for targeted data extractionAdvanced algorithms for determining reading order in complex formatsProprietary table structure recognition and parsing capabilitiesFine-tuned vision-language models for interpreting charts, tables, and figuresIf you are passionate about the convergence of computer vision, natural language processing, and data infrastructure, your contributions at Pulse will directly influence our customers and shape the future of document intelligence.

Jul 30, 2025
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companyHandshake logo
Full-time|On-site|San Francisco, CA

Join Handshake as an Associate Machine Learning Engineer and embark on an exciting journey in the world of artificial intelligence and machine learning. In this role, you will collaborate with a talented team to develop innovative solutions that leverage cutting-edge technologies. You'll have the opportunity to contribute to real-world projects, enhancing your skills while driving impactful results.

Apr 2, 2026
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companyAxiom Bio logo
Full-time|On-site|SF Global HQ

Charter:Join us as a pivotal member of a groundbreaking team dedicated to revolutionizing the field of toxicology by developing advanced AI systems that will replace traditional lab and animal experiments.What We Seek:We are on the lookout for exceptional individuals who can inspire those around them and drive the team towards greatness. Our ideal candidate is someone with high agency—able to identify priorities and take action. We value unique passions and hobbies that may seem niche but reveal a deep commitment and curiosity when explored. Candidates should approach challenges with both intentionality and a sense of wonder, embodying the spirit of exploration akin to an immigrant in a new land or a self-taught coder. A strong desire to learn and grow, coupled with technical excellence and a commitment to mastering one’s craft, is essential. We want those who are willing to tackle daunting challenges and derive satisfaction from the journey as much as the outcome.Your Responsibilities:Establish the foundational end-to-end ML/AI system, including wetlab data generation, data cleaning/processing, model architecture, training, inference, and deployment strategies.Lead innovative research and development initiatives focused on elucidating the interplay between chemistry and biology.Design and scale large models that are pretrained on paired chemistry and biological imagery.Conduct applied research aimed at optimizing, aggregating, and pooling embeddings.Become a thought leader in emerging and underexplored domains, such as molecular graph representations and generative diffusion for biological applications.Develop entrepreneurial skills alongside engineering expertise by creating impactful solutions that deliver substantial value for scientists.Deliver outstanding technology and products that redefine industry standards.Preferred Attributes:...

Nov 14, 2025
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companyUnitX Labs logo
Full-time|On-site|HQ

Position: Machine Learning EngineerAbout Us:At UnitX, we are pioneering the development of cutting-edge physical AI systems designed to automate repetitive visual tasks within manufacturing environments. Our dynamic startup thrives on a diverse team of experts from renowned institutions such as Stanford, MIT, and Google. To date, we have successfully implemented over 1,000 mission-critical AI systems across more than 190 of the world's top manufacturing production lines. Annually, our AI inspection systems oversee the quality of products valued at $15 billion.Join us for a unique opportunity to contribute to groundbreaking computer vision technologies that are transforming global manufacturing efficiency.Your Responsibilities:Design and implement innovative algorithms to analyze raw sensor data for defect detection, focusing on pixel-level precision in high-resolution image and 3D data segmentation.Develop robust software solutions that operate continuously on production lines, executing our algorithms in real-time with decision-making latency under 20ms.Create metrics and tools for comprehensive model performance evaluation, enhancing system visibility and interpretability.Research and explore novel methodologies, pushing the boundaries of AI technology, including Stable Diffusion and SAM, to deliver critical applications in manufacturing.Who You Are:Bachelor's degree in Computer Science, Mathematics, Physics, or a related technical discipline, or equivalent experience showcasing solid mathematical foundations.A minimum of 2 years of experience developing machine learning models focused on computer vision applications in production settings.Deep understanding of Deep Learning theories and practical applications, with proficiency in frameworks such as PyTorch or TensorFlow. Strong Python programming skills for creating efficient, maintainable solutions within extensive codebases.Excellent communication and decision-making abilities, able to articulate experimental rationale and judiciously navigate between exploration and exploitation strategies.Demonstrated resilience and adaptability in complex, uncertain environments.Preferred Qualifications:Experience with large-scale data processing and algorithm optimization.Familiarity with tools for machine learning and data visualization.

Apr 3, 2026
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companyHive logo
Full-time|On-site|San Francisco

Join Hive as a Senior Machine Learning Engineer and help shape the future of AI! We are seeking passionate individuals who excel at developing and deploying cutting-edge deep learning models. In this role, you will work with large-scale datasets to create innovative machine learning solutions, collaborating closely with a talented team of engineers to push the boundaries of artificial intelligence. Ideal candidates will have a proven track record of building and scaling machine learning projects from conception to production, along with a strong commitment to continuous learning and personal ownership in their work.

Dec 10, 2021
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company
Full-time|On-site|San Francisco, CA

Be Part of the Future of Autonomous RoboticsAt Bedrock Robotics, we are pioneering the transition of AI from theoretical frameworks to practical applications in the built environment. Our team is comprised of seasoned professionals who have been instrumental in the success of innovative companies such as Waymo, Segment, and Uber Freight. We are at the forefront of deploying autonomous technologies in heavy construction machinery, significantly enhancing the efficiency and safety of multi-billion dollar infrastructure projects across the nation.With backing from $350 million in funding, our mission is to address the urgent need for housing, data centers, and manufacturing facilities, while simultaneously responding to the construction industry's labor shortages.This position is where cutting-edge algorithms meet the practical world of construction. You will work alongside industry experts and top-tier engineers to tackle complex real-world challenges that cannot be simulated. If you are eager to leverage advanced technology for impactful problem-solving within a skilled team, we encourage you to apply.

Jan 31, 2026
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companySpecter logo
Full-time|On-site|San Francisco

Company Overview At Specter, we are pioneering a software-defined "control plane" designed to enhance the real-world perception of physical assets. Our mission begins with safeguarding American businesses by providing them with comprehensive insights into their physical environments.To achieve this, we are developing a robust hardware-software ecosystem leveraging multi-modal wireless mesh sensing technology. This innovation allows us to significantly reduce the cost and time involved in sensor deployment by a factor of ten. Ultimately, our platform aims to serve as the perception engine for businesses, facilitating real-time visibility and autonomous management of their operational perimeters.Our co-founders, Xerxes and Philip, are deeply committed to empowering our partners in the rapidly evolving landscape of physical AI and robotics. We are a dynamic, rapidly expanding team comprised of talent from Anduril, Tesla, Uber, and the U.S. Special Forces.Position Overview Specter is seeking a dedicated Machine Learning Infrastructure Engineer to construct and optimize the ML systems that drive real-time perception and inference capabilities across our edge-cloud platform. This position will involve overseeing the training, deployment, and enhancement of computer vision and sensor fusion models, aimed at enabling autonomous monitoring and decision-making for our clients' physical assets.Key Responsibilities Include:Design and implement scalable ML training pipelines for computer vision applications, including object detection, tracking, classification, and segmentation.Develop efficient model serving infrastructures to facilitate real-time inference on edge devices with limited computational and power resources.Optimize models for deployment on embedded hardware, employing techniques such as quantization, pruning, TensorRT, ONNX, and CoreML.Create continuous training and evaluation systems to enhance model performance through feedback loops derived from production data.Establish data pipelines for the ingestion, labeling, versioning, and management of extensive multi-modal sensor datasets, including video, radar, lidar, and thermal data.Implement model monitoring frameworks, A/B testing methodologies, and performance analytics for deployed perception systems.Collaborate with perception researchers to transition models from research environments to scalable production across thousands of edge nodes.Construct tools and infrastructure for distributed training, hyperparameter optimization, and experiment tracking.

Oct 3, 2025

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