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As a Google Vertex Full Stack Software Engineer, you will be responsible for developing and implementing machine learning models using Google Vertex AI and developing consumable API microservices using Typescript, Node.js, Express.
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Develop and implement train machine learning models using Google Vertex AI and Typescript, Express. Design, build, deploy machine learning models and microservices on the Google Cloud Platform.
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We are seeking a Full-Stack Software Engineer (Google Vertex) to join our team and transform ford.com into a customer engagement platform with modern designs and best-in-class experience.
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Optimize and fine-tune machine learning models for performance and efficiency. 1 + years of experience in machine learning engineering or a related field. Stay updated on the latest advancements in machine learning and AI technologies.
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Collaborate with data scientists and engineers to design, build, and maintain Azure-based MLOps pipelines for automating machine learning model deployment, monitoring, and maintenance. Implement Azure-based deployment pipelines for deploying machine learning models into production environments.
$135,000 - $140,000 a yearFull-timeExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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2 + years of experience with developing REST APIs with progressive responsibilities in software development in a scaled agile environment with Typescript, Node.js. Ability to collaborate well with software engineers, designers, and business partners.
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Familiarity with Front-end web development technologies (React, Vue.js, Angular, etc.) 2 + years of experience with developing microservices and implementing CI/CD pipelines via cloud computing services like (Google Cloud Platform preferred), AWS, Azure or similar.
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Js, Koa or other Back-end frameworks. Flexible family care, parental leave, new parent ramp-up programs, subsidized back-up childcare and more. Advance use of Natural Language Processing including the extensive use of Large Language Models for text analysis.
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Work with top-flight software, systems, and mechanical engineering talent from places like Google, Palantir, and NASA JPL.Own entire projects while working alongside cross-functional teams of physicians, designers, and operators.
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2 + years of experience with React, Angular or other Front-end web development technologies. Familiarity with REST APIs and Cloud architectures (Google Cloud Platform) Understanding of Release Management, Source Code repository management, CI/CD practices and tools (GitHub, Maven, Jenkins etc.
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Master’s degree in Computer science with ML as a focus, Computer Engineering, Electrical Engineering or related field. Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering or related field or a combination of education and equivalent work experience.
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As a Senior Machine Learning Engineer, You Will Be Building a Platform That Accelerates Drug Discovery With Machine Learning For a Wide Variety Of Use Cases With Respect To Data Modality, Model Architecture, And Model Size. By Leveraging Your Experience In Machine Learning, Software Engineering, Infrastructure, And Data, You Will.
$170,000 - $192,000 a yearFull-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Will your career be a deep dive into what you love, or a series of new teams and new skills? Experience with lightweight product development methods such as user story mapping or rapid prototyping. You will work closely with cross-functional teams, including UX/UI designers, business analysts, and product managers, to create innovative digital solutions that drive engagement and increase customer satisfaction.
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At least 2 years of relevant experience deploying machine learning models & software to cloud scale environments. 4+ years of experience implementing and applying algorithms for machine learning and artificial intelligence.
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Experience defining product vision, strategy, product roadmaps and creating and managing backlogs (Rally, JIRA or similar) Visa sponsorship is available for this position. 2 + years of experience working with SQL, NoSQL databases, and big data platforms.
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