{"schemaVersion":"jobsearcher.job.v1","id":"4010435b5da43d474fb22bac","url":"https://jobsearcher.com/jobs/4010435b5da43d474fb22bac","canonicalUrl":"https://jobsearcher.com/jobs/4010435b5da43d474fb22bac","title":"Staff Machine Learning Engineer","description":"As a Staff Machine Learning Engineer at Labelbox, you will be a technical leader for the team building a scalable AI platform that uses foundation models for real-world AI applications. You will be responsible for prototyping and developing production grade tools for model fine tuning, evaluation, experimentation, metrics and quality control, and alignment with human or AI feedback. You will draw on your expertise in machine learning, natural language processing, and deep learning, and how various Foundation Models, including multi-modal models, embody these technologies, to drive the success of our AI initiatives in terms of roadmap definition, architecture decisions and execution, delivering products that meet the needs of our customers.\r\nYour Day to Day\r\nEnhance and improve Labelbox’s core machine learning capabilities, including model registry, training and inferencing, towards making it a best-in-class AI Platform-as-a-Service. Examples include improving inference latency or optimizing training memory consumption.\r\nConduct feasibility studies and prototype development for new applications leveraging foundation models.\r\nResearch design, and incorporate approaches and metrics for evaluating generated output from models, including human-preference metric, e.g. ranking and selection and other types, e.g. model performance variance with ELO scores.\r\nProvide guidance to other engineering teams on best practices for leveraging machine learning, specifically using Labelbox’s AI engine as a PaaS.\r\nMentor and guide less experienced engineers while driving initiatives towards completion.\r\nGuide customers and the broader Labelbox community with best practices in AI using Foundation Models, through meetings, PoC applications, webinars, blog posts, etc.\r\nOversee and define mechanisms for adaptation, hyperparameter tuning and fine-tuning of foundation models to suit specific application requirements.\r\nEngage with stakeholders, including customers, to understand their needs, gather requirements, and provide expert advice on AI-driven solutions.\r\nStay abreast of industry trends, emerging technologies, and advancements in foundation models and their applications. Analyze, assess and incorporate technologies coming out of various AI research labs.\r\nContribute to technical documentation, research publications, blog posts, and presentations at conferences and forums.\r\nAbout You\r\nBachelor’s degree in computer science or related field. Advanced degree preferred.\r\n5+ years of work experience in a software company in the domain of distributed systems, ML engineering, AI/ML infrastructure or platforms.\r\nExtensive software design and architecture skills in large-scale systems and AI/ML systems design.\r\nProven experience in developing and implementing large-scale systems that integrate with Foundation Models for real-world applications.\r\nExperience with various types of foundation models and multi-modal models.\r\nExperience with machine learning algorithms, natural language processing, and deep learning frameworks.\r\nExperience working on Generative AI, including model fine-tuning, experimentation, metrics for model evaluation, monitoring and quality-control.\r\nStrong understanding of AI agents architecture, RLHF, building and/or using ML pipelines for training and inference.\r\nAn understanding of transformers and LLM architecture.\r\nGood grasp of the overall Data + AI ecosystem, including data processing technologies.\r\nProficiency in programming languages such as Python, Typescript, or Java.\r\nDemonstrated ability to keep up with industry trends and research in the AI/ML landscape.\r\nExcellent communication and collaboration skills.\r\nThrive in a fast-paced environment with willingness and ability to dive deep.\r\nComfortable with ambiguity and able to break-down high level requirements into actionable tasks in a methodical manner.\r\nResourceful, creative, problem-solver with an attention to detail who will not hesitate to take initiative and get things done.\r\nEngineering at Labelbox\r\nWe build a comprehensive platform and end-to-end tool suite for AI system development. We believe in providing the best user experience at scale with high quality. Our customers use our platform in production environments, daily, to build and deploy AI systems that have a real positive impact in the world.\r\nWe believe in collaborative excellence and shared responsibility with decision making autonomy wherever possible. We strive for a great developer experience with continuous fine tuning. How we work is one of the cornerstones of engineering excellence at Labelbox.\r\nWe learn by pushing boundaries, engaging in open debate to come up with creative solutions, then committing to execution. We continuously explore and exploit new technologies, creating new and perfecting existing techniques and solutions. Making customers win is our North Star.\r\nLabelbox strives to ensure pay parity across the organization and discuss compensation transparently. The expected annual base salary range for United States-based candidates is below. This range is not inclusive of any potential equity packages or additional benefits. Exact compensation varies based on a variety of factors, including skills and competencies, experience, and geographical location.\r\nAnnual base salary range\r\n$215,000—$250,000 USD\r\nExcel in a remote-friendly hybrid model.\r\nWe are dedicated to achieving excellence and recognize the importance of bringing our talented team together. While we continue to embrace remote work, we have transitioned to a hybrid model with a focus on nurturing collaboration and connection within our dedicated tech hubs in the San Francisco Bay Area, New York City Metro Area, and Wrocław, Poland. We encourage asynchronous communication, autonomy, and ownership of tasks, with the added convenience of hub-based gatherings.\r\nYour Personal Data Privacy: Any personal information you provide Labelbox as a part of your application will be processed in accordance with Labelbox’s Job Applicant Privacy notice.\r\nAny emails from Labelbox team members will originate from a @labelbox.com email address. If you encounter anything that raises suspicions during your interactions, we encourage you to exercise caution and suspend or discontinue communications. If you are uncertain about the legitimacy of any communication you have received, please do not hesitate to reach out to us at recruiting@labelbox.com for clarification and verification.#J-18808-Ljbffr","company":"Labelbox","rawCompany":"labelbox","city":"Millbrae","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-09-23T01:14:13.358Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-scientists"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Staff Machine Learning Engineer","description":"As a Staff Machine Learning Engineer at Labelbox, you will be a technical leader for the team building a scalable AI platform that uses foundation models for real-world AI applications. You will be responsible for prototyping and developing production grade tools for model fine tuning, evaluation, experimentation, metrics and quality control, and alignment with human or AI feedback. You will draw on your expertise in machine learning, natural language processing, and deep learning, and how various Foundation Models, including multi-modal models, embody these technologies, to drive the success of our AI initiatives in terms of roadmap definition, architecture decisions and execution, delivering products that meet the needs of our customers.\r\nYour Day to Day\r\nEnhance and improve Labelbox’s core machine learning capabilities, including model registry, training and inferencing, towards making it a best-in-class AI Platform-as-a-Service. Examples include improving inference latency or optimizing training memory consumption.\r\nConduct feasibility studies and prototype development for new applications leveraging foundation models.\r\nResearch design, and incorporate approaches and metrics for evaluating generated output from models, including human-preference metric, e.g. ranking and selection and other types, e.g. model performance variance with ELO scores.\r\nProvide guidance to other engineering teams on best practices for leveraging machine learning, specifically using Labelbox’s AI engine as a PaaS.\r\nMentor and guide less experienced engineers while driving initiatives towards completion.\r\nGuide customers and the broader Labelbox community with best practices in AI using Foundation Models, through meetings, PoC applications, webinars, blog posts, etc.\r\nOversee and define mechanisms for adaptation, hyperparameter tuning and fine-tuning of foundation models to suit specific application requirements.\r\nEngage with stakeholders, including customers, to understand their needs, gather requirements, and provide expert advice on AI-driven solutions.\r\nStay abreast of industry trends, emerging technologies, and advancements in foundation models and their applications. Analyze, assess and incorporate technologies coming out of various AI research labs.\r\nContribute to technical documentation, research publications, blog posts, and presentations at conferences and forums.\r\nAbout You\r\nBachelor’s degree in computer science or related field. Advanced degree preferred.\r\n5+ years of work experience in a software company in the domain of distributed systems, ML engineering, AI/ML infrastructure or platforms.\r\nExtensive software design and architecture skills in large-scale systems and AI/ML systems design.\r\nProven experience in developing and implementing large-scale systems that integrate with Foundation Models for real-world applications.\r\nExperience with various types of foundation models and multi-modal models.\r\nExperience with machine learning algorithms, natural language processing, and deep learning frameworks.\r\nExperience working on Generative AI, including model fine-tuning, experimentation, metrics for model evaluation, monitoring and quality-control.\r\nStrong understanding of AI agents architecture, RLHF, building and/or using ML pipelines for training and inference.\r\nAn understanding of transformers and LLM architecture.\r\nGood grasp of the overall Data + AI ecosystem, including data processing technologies.\r\nProficiency in programming languages such as Python, Typescript, or Java.\r\nDemonstrated ability to keep up with industry trends and research in the AI/ML landscape.\r\nExcellent communication and collaboration skills.\r\nThrive in a fast-paced environment with willingness and ability to dive deep.\r\nComfortable with ambiguity and able to break-down high level requirements into actionable tasks in a methodical manner.\r\nResourceful, creative, problem-solver with an attention to detail who will not hesitate to take initiative and get things done.\r\nEngineering at Labelbox\r\nWe build a comprehensive platform and end-to-end tool suite for AI system development. We believe in providing the best user experience at scale with high quality. Our customers use our platform in production environments, daily, to build and deploy AI systems that have a real positive impact in the world.\r\nWe believe in collaborative excellence and shared responsibility with decision making autonomy wherever possible. We strive for a great developer experience with continuous fine tuning. How we work is one of the cornerstones of engineering excellence at Labelbox.\r\nWe learn by pushing boundaries, engaging in open debate to come up with creative solutions, then committing to execution. We continuously explore and exploit new technologies, creating new and perfecting existing techniques and solutions. Making customers win is our North Star.\r\nLabelbox strives to ensure pay parity across the organization and discuss compensation transparently. The expected annual base salary range for United States-based candidates is below. This range is not inclusive of any potential equity packages or additional benefits. Exact compensation varies based on a variety of factors, including skills and competencies, experience, and geographical location.\r\nAnnual base salary range\r\n$215,000—$250,000 USD\r\nExcel in a remote-friendly hybrid model.\r\nWe are dedicated to achieving excellence and recognize the importance of bringing our talented team together. While we continue to embrace remote work, we have transitioned to a hybrid model with a focus on nurturing collaboration and connection within our dedicated tech hubs in the San Francisco Bay Area, New York City Metro Area, and Wrocław, Poland. We encourage asynchronous communication, autonomy, and ownership of tasks, with the added convenience of hub-based gatherings.\r\nYour Personal Data Privacy: Any personal information you provide Labelbox as a part of your application will be processed in accordance with Labelbox’s Job Applicant Privacy notice.\r\nAny emails from Labelbox team members will originate from a @labelbox.com email address. If you encounter anything that raises suspicions during your interactions, we encourage you to exercise caution and suspend or discontinue communications. If you are uncertain about the legitimacy of any communication you have received, please do not hesitate to reach out to us at recruiting@labelbox.com for clarification and verification.#J-18808-Ljbffr","datePosted":"2026-09-23T01:14:13.358Z","dateModified":"2026-09-23T01:14:13.358Z","hiringOrganization":{"@type":"Organization","name":"Labelbox","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"4010435b5da43d474fb22bac"},"url":"https://jobsearcher.com/jobs/4010435b5da43d474fb22bac"}}