Cloud Machine Learning Evangelist - Remote (US)

At Hugging Face, we are dedicated to making AI accessible to everyone. We have developed the fastest-growing platform for AI creators, boasting over 11 million users who have collectively contributed more than 2 million models, 700,000 datasets, and 600,000 applications. Our open-source libraries have gained over 600,000 stars on GitHub.About the RoleAs a Cloud Machine Learning Evangelist, you will play a pivotal role in enhancing the influence of the Hugging Face ML Cloud team. Your mission is to educate machine learning practitioners on how they can optimize their training and inference workloads.The Hugging Face ML Cloud team collaborates strategically with leading cloud providers (AWS, GCP, Azure, Cloudflare), AI accelerators (including NVIDIA, AMD, Intel, Gaudi, Inferentia, TPU), and system integrators (Dell, Nutanix) to facilitate the use of Hugging Face models and libraries across these platforms.These partnerships are essential to our strategy as an open platform (ensuring no customer lock-in) and our monetization approach to enhance usage and revenue for our partners through commercial collaborations and product extensions.This role is distinct from marketing or business development; your focus will be on increasing visibility and usage of integrations with strategic partners through various activities such as:Writing technical blog postsEnhancing documentation and providing code examplesPresenting to both business and technical audiences at partner conferencesEngaging in or facilitating webinarsCreating and promoting demosLeading go-to-market discussions with strategic partnersYou will be at the cutting edge of Generative AI, exploring practical applications with open-source technologies. This role offers significant autonomy and creative freedom, aiming for a tenfold impact compared to similar positions in large tech companies.About YouYou are enthusiastic about ML Engineering, developing actionable AI applications, and optimizing them for the cloud. Your passion for learning new engineering concepts and technologies is evident, and you enjoy discussing these topics with peers. You value a positive Developer Experience and take pride in writing easily comprehensible code.Excellent communication skills are vital, and you are comfortable speaking publicly to technical audiences. You engage positively with the ML community, and existing involvement in platforms such as GitHub, LinkedIn, Twitter, Reddit, or other educational channels is expected. Experience in Open Source development will be advantageous.More about Hugging FaceWe are actively working to create a culture that values diversity, equity, and inclusion.We are committed to building a team that reflects a variety of backgrounds and perspectives, fostering a collaborative atmosphere where all voices are heard.

About BasisBasis is a pioneering nonprofit organization dedicated to applied AI research, driven by two key objectives.The first objective is to comprehend and develop intelligence. This encompasses establishing the mathematical foundations of reasoning, learning, decision-making, understanding, and explanation, while also creating software that embodies these principles.The second objective is to enhance society’s capacity to tackle complex challenges. This involves broadening the scope, scale, and complexity of problems we can address today, and crucially, accelerating our capacity to solve future problems.To fulfill these missions, we are constructing an innovative technological infrastructure inspired by human reasoning, along with a collaborative organization that prioritizes human values.About the RoleAs an ML Systems Engineer at Basis, you will ensure that our training and evaluation infrastructure is fast, reliable, and scalable. You will manage the entire stack, from distributed training frameworks to cloud administration, enabling researchers to rapidly iterate on complex models while efficiently managing computational resources.We are seeking engineers who possess a profound understanding of ML systems paired with operational excellence. The ideal candidate will have experience in distributed training at scale, expertise in debugging numerical instabilities, and the ability to manage cloud infrastructure that seamlessly transitions from experimentation to production. You will be the steward of training stability, an optimizer of computational costs, and a facilitator of reproducible research.This position encompasses both traditional ML engineering and cloud/DevOps responsibilities. You will oversee GPU clusters, optimize cloud expenditures, ensure security and compliance, and build the infrastructure that allows researchers to focus on algorithms rather than operations.We are looking for individuals who are committed to developing robust ML infrastructure, maintaining a culture of documentation for issues and solutions, and prioritizing operational excellence as a core value.

About the RoleAt Zencastr, we are dedicated to creating innovative end-to-end AI systems and core microservices that revolutionize the podcasting landscape. By harnessing the latest technologies, we aim to enhance the user experience for millions of podcast creators and listeners every day.We invite an exceptional Senior Machine Learning Engineer to become a vital member of our dynamic team. In this role, you will engage in large-scale machine learning projects aimed at enriching the podcast creation journey for Zencastr users.You will collaborate with a group of dedicated engineers who are enthusiastic about understanding the factors that influence long-term user satisfaction with Zencastr. Your contributions will help shape our recommendations and content strategies. As a key player in the team, you will work alongside research scientists and data professionals to prototype and implement cutting-edge machine learning solutions that intertwine speech processing with user satisfaction.Key ResponsibilitiesDesign, research, and develop pioneering machine learning applications and algorithms to enhance the experiences of podcasters and their audiences globally.Collaborate with cross-functional teams to create new product features that enhance Zencastr's machine learning services.Advance audio and text capabilities within the machine learning team.Engage with leading experts in signal processing.Ideal Candidate ProfileA Master's degree or higher in Machine Learning, Mathematics, Computer Science, or a related quantitative discipline.A minimum of 5 years of experience in Python programming.At least 3 years of experience in machine learning research, particularly with a focus on speech processing.3+ years of experience in training and deploying neural networks.Extensive experience with machine learning frameworks such as PyTorch, TensorFlow, and Scikit-Learn.Proficiency in building and maintaining production-ready machine learning systems.Ability to lead the design and implementation of significant software components and features.A passion for rapidly building model prototypes.Familiarity with cloud platforms such as Google Cloud, AWS, or Modal.A proactive mindset with the ability to spearhead projects and foster positive collaborations with partners and colleagues.

Location: New York, NYStart date: ASAPLanguages: English (required)About the RolePragmatike is partnering with a rapidly expanding AI cybersecurity firm, supported by premier investors and leading AI experts. This innovative company is constructing the security framework for the AI age, safeguarding organizations against AI-driven threats like deepfakes, smishing, and synthetic voice attacks.After securing significant Series B funding from top-tier AI and venture capital partners, the firm is poised for an essential growth stage. With trust from major banking institutions, tech companies, and healthcare entities, they are accelerating their scaling efforts to fulfill enterprise demand in a market exceeding $200 billion.We seek a Director of Machine Learning to architect and develop the company’s machine learning capabilities from inception. This role is pivotal to our product vision, emphasizing strategic ownership, infrastructure establishment, and the execution of machine learning throughout the organization.Currently, there is no dedicated ML infrastructure or team in place. You will lay the groundwork: identifying where ML creates product value, designing comprehensive production systems, and guiding the technical evolution of ML across the company.This is a high-impact, autonomous position ideal for someone experienced in building ML systems in operational environments and ready to scale an ML function from the ground up.What You Will DoDefine the ML strategy for the company: determining application areas for ML across products, required infrastructure, and the approach for build versus buy decisions.Design and develop end-to-end production ML systems, including data pipelines, model training workflows, assessment frameworks, and inference serving.Establish a robust evaluation methodology to assess model quality, identify regressions, and facilitate data-driven improvements.Oversee the data strategy: identifying necessary data, establishing labeling processes, structuring feedback loops, and ensuring continuous model enhancement.Collaborate closely with product and backend engineering teams to seamlessly integrate ML into customer-facing systems.Produce high-quality code within the existing codebase and contribute to architectural decisions.As the function expands, support recruitment, mentorship, and leadership of the ML team.

Who is Nexxen?Nexxen is revolutionizing the advertising landscape with a data-driven approach that empowers advertisers, agencies, publishers, and broadcasters globally. Our innovative technology framework unifies a demand-side platform (DSP) and supply-side platform (SSP), anchored by the Nexxen Data Platform, to deliver meaningful advertising solutions.Why become a part of the Nexxen team?Join us in our mission to transform advertising through our flexible and creative solutions. At Nexxen, we value a culture that emphasizes the 3Cs - Customer Centricity, a Curious Mindset, and Collaboration without Ego. Become part of a dynamic team that thrives on commitment and ingenuity.Your Safety is Our PriorityAt Nexxen, we prioritize the safety and well-being of our employees. We are vigilant against online scams and fraudulent job postings. Please note that we will never ask for payment as a condition of employment or promote dubious financial schemes. If you encounter any suspicious communications, contact us at infosec@nexxen.com. Your trust is paramount; stay safe and informed.Position OverviewAs a Senior Machine Learning Engineer, you will join our Applied Data Science group within the Nexxen DSP Software Development team. This hands-on role involves collaborating closely with data scientists to develop cutting-edge data science infrastructure aimed at real-time performance optimization and machine learning applications. The ideal candidate will possess extensive experience in implementing machine learning technologies or data-driven algorithms, and should display a proactive and innovative mindset.We operate in a hybrid model, with team members working three days a week at our New York office and remotely for the remainder of the week.Key Responsibilities:Design and develop high-performance, large-scale services for Nexxen DSP programmatic integrations and platform products.Drive innovative solutions and implement machine learning algorithms for enhanced performance.

Why Choose Charlie Health?Across the nation, countless individuals are facing mental health challenges, substance use disorders, and eating disorders. Unfortunately, many encounter obstacles to obtaining the care they need, such as limited local options and lengthy wait times. Behavioral healthcare often fails to provide the personalized support that individuals require, leaving them feeling overlooked and unsupported.At Charlie Health, our mission is to transform this landscape. We strive to connect individuals to crucial behavioral health treatment through personalized, virtual care that fosters connections between clients and clinicians, care teams, loved ones, and their supporting communities. By prioritizing those with complex needs, we are enhancing access to significant care and achieving improved outcomes—all from the comfort of home.As a rapidly expanding organization, we are reaching more communities daily, and we are assembling a team dedicated to redefining behavioral health treatment. If you are eager to leverage your skills to create meaningful change and help individuals access the care they deserve, we invite you to join us.About the RoleCharlie Health is a leader in high-acuity virtual behavioral care, having provided life-saving treatment to over 100,000 clients across the nation. Our Matching and Outcomes team is responsible for developing products that assess and enhance clinical outcomes, including systems for provider recommendations and clinical decision support tools, ensuring effective treatment. You will design predictive models and workflows to connect patients with the most suitable therapists and peers, enabling clinicians to customize care to meet each client's unique needs. The systems you develop will empower clinicians to condense and synthesize insights from our clients and providers into actionable guidance at every step. If you are passionate about utilizing data-driven insights to enhance outcomes, this team is for you.

Join headway as a Senior Machine Learning Engineer and make a significant impact in the field of machine learning and artificial intelligence. In this role, you will leverage your expertise to develop innovative solutions, improve existing algorithms, and collaborate with cross-functional teams to drive forward our mission of transforming the healthcare experience.

Join Hang in Shaping the Future of Brand Loyalty!Hang is at the forefront of revolutionizing brand loyalty and membership platforms. Our innovative approach combines personalization, gamification, and a robust integration ecosystem to deliver an unparalleled loyalty experience for customers.We proudly partner with an array of prominent brands including Ulta Beauty, Budweiser, and Flipkart, as well as renowned restaurant chains like Boba Guys and Roam Artisan Burger.Our team comprises experts from leading tech companies such as Google, Amazon, Apple, and Meta, bringing years of specialization in loyalty programs, game design, and finance.With a successful $16 million Series A funding round led by Paradigm, alongside notable investors like Tiger Global and Kevin Durant, Hang is poised for rapid growth and innovation.About the RoleWe are on the lookout for a talented and forward-thinking Machine Learning Engineer to enhance our platform's capabilities. This role will be pivotal in developing and implementing machine learning models that contribute to our product development and foster data-driven decision-making.What You’ll DoModel Development: Create, build, and deploy innovative machine learning models to optimize customer personalization, predictive analytics, and automated decision-making processes.Data Analysis: Conduct thorough analysis of extensive datasets to uncover trends and insights that will inform model development and strategic business initiatives.Algorithm Optimization: Regularly test and refine algorithms to ensure peak accuracy and operational efficiency.Collaborative Development: Collaborate closely with software engineers, data scientists, and product managers to seamlessly integrate ML models into our platform.Research and Innovation: Keep abreast of the latest trends in machine learning and AI, exploring new technologies that can advance Hang's offerings.Technical Leadership: Provide expertise and guidance on machine learning best practices, contributing to the strategic direction of our technology initiatives.

At Hugging Face, we are committed to democratizing artificial intelligence. Our platform is rapidly becoming the go-to resource for AI developers, boasting over 11 million users who have collaboratively shared more than 2 million models, 700,000 datasets, and 600,000 applications. Our open-source libraries have received over 600,000 stars on GitHub.About the RoleAs an Open-Source Machine Learning Engineer, you will play a pivotal role in enhancing the open-source machine learning ecosystem. Your primary focus will be on improving existing libraries such as Transformers, Datasets, and Accelerate. You’ll collaborate with a diverse array of users and contributors in this vibrant community. We believe in fostering your interests and will work with you to ensure your contributions are impactful.In this role, you will help nurture one of the most active machine learning communities, guiding users in leveraging and contributing to the tools you develop. Daily interactions with researchers, ML practitioners, and data scientists will take place via GitHub, our forums, and Slack.About YouIf you have a passion for open-source projects and are eager to simplify complex technologies for broader audiences, we are excited to receive your application! We encourage candidates who may not meet every qualification to apply, as we seek to build a diverse team with complementary skills and experiences.More about Hugging FaceCommitment to Diversity and Inclusion: We actively cultivate a workplace that respects and supports all individuals, regardless of background. This commitment is essential to creating a thriving community and company.Employee Development: You will collaborate with some of the brightest minds in the industry. We prioritize impact and continuous growth, offering reimbursement for relevant conferences, training, and education.Well-being Initiatives: We support flexible work hours and remote work options. Health, dental, and vision benefits are available for employees and their dependents, along with parental leave and flexible paid time off.Remote Work Support: Although we have offices in NYC and Paris, we are a distributed team, allowing remote employees to visit our offices. We will also provide the necessary equipment to ensure your success.

Join SoundCloud, a leading platform that enables artists and fans to connect and share their passion for music. Established in 2007, our artist-first approach empowers creators to develop their careers with innovative tools, services, and resources. With a catalog featuring over 400 million tracks from 40 million artists, the future of music is unfolding at SoundCloud. We are seeking a Senior Machine Learning Engineer to become an integral member of our Reco-Core team. This role presents an exciting opportunity to influence and steer the machine learning initiatives for one of SoundCloud's most essential product areas. You will collaborate closely with machine learning, data, and backend engineers to design, implement, and deploy models that facilitate music discovery for millions of users across our extensive audio catalog.Key Responsibilities:Create and deploy comprehensive machine learning solutions for recommendation systems, focusing on candidate generation, personalization, user and item modeling, and ranking algorithms.Oversee the entire machine learning lifecycle, from prototyping and evaluation to deploying scalable models and monitoring performance in production.Enhance and expand the foundation for ML engineering and MLOps within the Reco-Core team, establishing best practices and developing tools for rapid iteration.Collaborate with analysts and data scientists to convert research findings into production-ready systems.Work alongside fellow ML engineers to utilize shared infrastructure and collective expertise.

Dandy is building technology to modernize dental practices, with a focus on delivering tools and support that help clinicians and their teams. Backed by leading venture capital firms, the company aims to create the operating system for dental offices worldwide. In this Senior Software Engineer I, Machine Learning Platform role, the focus is on bridging advanced computer vision research with reliable, production-ready systems. The position centers on designing and scaling infrastructure for large 3D datasets, orchestrating training pipelines, and supporting robust generative model deployments. Role overview Work closely with Machine Learning Engineers to build training pipelines that manage large 3D datasets, support model training, and enable ongoing model improvements. Refine internal ML components to streamline the lifecycle from data labeling and experimentation through deployment, reducing technical debt along the way. Develop and maintain cloud-native systems and tools, particularly using GCP and Kubernetes, to support the company’s 3D dental products with a focus on security, efficiency, and performance. Write clean, maintainable code and tests that align with internal best practices. Collaborate with stakeholders across Engineering to set long-term architectural goals and uphold high standards for quality. Requirements At least 5 years of experience as a Machine Learning Engineer or Software Engineer, ideally in a startup setting. Deep experience building and maintaining ML Platform components such as feature stores, model registries, or distributed training systems. Strong skills in Python-based ML frameworks like PyTorch or TensorFlow; familiarity with 3D geometric computer vision is a plus. Proven ability in large-scale data processing and developing ML data pipelines for complex model training. Strong problem-solving abilities and an interest in building solutions that improve system performance.

Machine Learning Developer Experience EngineerAbout Our TeamAt Adaptive ML, we are at the forefront of AI innovation, developing a cutting-edge Reinforcement Learning Operations (RLOps) platform that empowers enterprises to specialize and deploy Large Language Models (LLMs) with tangible outcomes. Our platform provides the foundational infrastructure needed to tune, evaluate, and serve specialized models at scale, enabling the pioneering of task-specific LLM development and the execution of production-ready workflows that manage millions of requests while optimizing for both cost and performance across distributed systems.Our dynamic team has previously contributed to the development of state-of-the-art open-access large language models. We successfully raised $20M in seed funding led by Index Ventures and ICONIQ in early 2024, and we are already operational with clients such as Manulife, AT&T, and Deloitte, spanning the travel and financial services sectors, with many more partnerships on the horizon.About This RoleWe are searching for a talented ML Developer Experience Engineer who will empower ML engineers and development teams to utilize reinforcement learning effectively, without needing extensive RL expertise. You will be responsible for creating developer-focused tools, abstractions, and workflows that simplify the training, evaluation, and deployment of RL models, making them intuitive, robust, and scalable. Your contributions will enhance our customers' ability to adopt, grow, and manage RL use cases independently.This position plays a crucial role in our growth strategy: your work will facilitate independent scaling for our customers, minimizing friction and enabling self-service adoption throughout their organizations. You will closely collaborate with Technical Success, Product, and Engineering teams to identify common patterns, extract reusable solutions, and delineate the boundaries between tooling and product.This position is based in Paris, New York, or Toronto.Your ResponsibilitiesDesign and build user-friendly SDKs, libraries, APIs, and tools that enhance RL workflows for developers and ML engineers.Achieve a balance between simplicity and flexibility—supporting common patterns while allowing for advanced configurations and extensibility.Collaborate with internal teams to refine core components into documented, reusable modules that drive customer success.Engage with technical and customer success teams to identify recurring customer patterns and workflow impediments.Translate user feedback into tooling enhancements, error messaging improvements, onboarding processes, and example references.Maintain comprehensive documentation to support user engagement.

Join our innovative Match Team as a Senior Machine Learning Engineer at Enigmaio, where you will play a pivotal role in developing advanced algorithms and models that enhance our matching capabilities. You will collaborate with cross-functional teams to design, implement, and optimize machine learning solutions that drive business outcomes.

Join Spotify as a Machine Learning Engineer and be at the forefront of innovation in music streaming. In this role, you will leverage cutting-edge machine learning algorithms and data-driven insights to enhance user experiences and drive business decisions. Collaborate with cross-functional teams to develop scalable solutions that improve our recommendation systems and user engagement.

Join our innovative team at Sunset Technologies as a Machine Learning Engineer. We are dedicated to pushing the boundaries of artificial intelligence and machine learning to deliver advanced solutions that enhance our products and services. You will be involved in designing, implementing, and optimizing machine learning models to analyze large datasets, develop predictive algorithms, and contribute to the overall growth of our technology stack.

Role Overview root-access is hiring a Machine Learning Engineer in New York City. This role works closely with the tech team to design and build machine learning algorithms that support and improve our products. The position involves hands-on development, data analysis, and delivering solutions that scale as our business grows. What You Will Do Develop machine learning models tailored to product needs Analyze complex data sets to extract insights and guide model improvements Create solutions that can scale to meet increasing demand Collaborate with engineers and product teams to integrate AI-driven features Who We’re Looking For Experience building and deploying machine learning algorithms Strong interest in artificial intelligence and its practical applications Ability to work with large, complex data sets Comfort working in a collaborative, evolving tech environment

Role Overview Spotify is hiring a Machine Learning Engineer focused on Personalization in New York, NY. This role centers on developing and applying machine learning algorithms to improve how users discover and enjoy music and podcasts. The work directly shapes the personalized experiences that keep listeners engaged and coming back. What You Will Do Design and implement machine learning models that tailor content recommendations to individual users Analyze user behavior and preferences to inform algorithm improvements Collaborate with product and engineering teams to integrate personalization features into the Spotify platform

Join Our Team as a Machine Learning Engineer! At FanDuel, we recognize that data is the lifeblood of our organization. As a Machine Learning Engineer, you will harness the power of our extensive real-time and relational datasets to drive insights that enhance user experiences. Your analytical skills will transform every interaction—from user clicks to game outcomes—into actionable intelligence, enabling us to make faster, more informed decisions that keep us ahead of the competition. Your role will be pivotal in fostering collaboration across teams. You will serve as the bridge between engineering teams, facilitating the development of our online applications while ensuring that essential data is available for feature engineering. Collaborating with Data Scientists and Analysts, you will help bring AI-driven insights into production and validate their effectiveness. Your efforts will be instrumental in organizing, modeling, and presenting data in a manner that provides a unified information structure, empowering FanDuel to respond intelligently to market dynamics and on-field events. If you are a Machine Learning Engineer with aspirations to thrive in a big data environment, we encourage you to apply! Your Responsibilities: Design and implement intelligent search systems incorporating typeahead search, vector search, and ML personalization to optimize user experience. Contribute to the creation of scalable serving systems for ML and GenAI/LLM models. Develop platform features and tools (e.g., CLI, SDK, Infrastructure Automation) that enhance the ML model lifecycle and GenAI/LLM application deployment. Utilize business intelligence tools such as Tableau, Knime, and Looker. Ensure data security and privacy compliance (e.g., GDPR, CPP). Implement data governance and testing frameworks. Support continuous integration and delivery of data products. Participate in an inclusive culture that prioritizes excellence, personal growth, and well-being.

Join Spotify's innovative team as a Machine Learning Engineer, where you'll be at the forefront of developing cutting-edge algorithms that enhance user experiences. In this role, you will leverage your expertise in machine learning to create scalable solutions and drive impactful projects that shape the future of music streaming.

Join Our Innovative TeamBecome a pivotal member of our team dedicated to creating the world's first biological reasoning model. Collaborate with us on groundbreaking generative foundational models that interpret biological systems across various scales—from molecular interactions to entire organisms—empowering us to predict, comprehend, and manipulate living systems like never before.Output is currently in stealth mode, driven by a team of seasoned founders and biotech experts who have successfully exited ventures in AI and biotechnology, supported by leading venture capital firms including Y Combinator.As a Machine Learning Engineer, you will partner with our founders and talented team members to innovate and deploy advanced AI solutions that facilitate intricate biological reasoning across diverse scales.Develop foundational models for biological systems capable of encoding and decoding biological data at scale.Create deep generative models tailored for biological applications, experimenting with innovative architectures to capture the complexities of multi-scale biological systems.Work on distributed training systems to scale our models to billions of parameters, focusing on performance and efficiency across multi-GPU and multi-node configurations while processing extensive biological datasets.Design efficient data pipelines to manage and process large biological datasets, tackling challenges in data loading, partitioning, and memory optimization.Establish and implement robust evaluation frameworks for complex biological models, ensuring data integrity and preventing leakage across dataset splits.