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Senior Software Engineer - Machine Learning Infrastructure

Company: LinkedIn
Location: Sunnyvale
Posted on: February 20, 2021

Job Description:

Senior Software Engineer Machine Learning InfrastructureLinkedIn was built to help professionals achieve more in their careers, and every day millions of people use our products to make connections, discover opportunities, and gain insights. Our global reach means we get to make a direct impact on the world's workforce in ways no other company can. We're much more than a digital resume we transform lives through innovative products and technology.Searching for your dream job? At LinkedIn, we strive to help our employees find passion and purpose. Join us in changing the way the world works.Machine learning powers the intelligence behind LinkedIn's products, including the feed, search ranking, ads placement, and job recommendations. The machine learning infrastructure team builds a machine learning platform, Pro-ML, that makes it easy for AI professionals to build, deploy, and maintain ML solutions. We are looking for engineers with a passion for making complex tasks simple for data scientists, AI engineers, and researchers. You will work alongside AI engineers to understand their approach and build software to enable their goals in a reproducible and error-free manner.As a software developer in Data, you will have first-hand opportunities to advance one of the most scalable AI platforms in the world. At the same time, you will work together with our talented teams of researchers and engineers to build your career and your personal brand in the AI industry.We are looking for engineers in each of the following areas:Deep LearningAdvance the TensorFlow ecosystem at LinkedIn, spanning deep learning model authoring, training, inference and serving infrastructure. Develop a deep understanding of TensorFlow internals and build tooling & automation to make TensorFlow interop seamlessly with LinkedIn's technology. You will encode best practices directly into our toolchain, guide users on proper use of TensorFlow, and contribute to the open source community. You will advance the state of the art at LinkedIn and across the software industry.Feature ManagementMake it easy for users to discover, access, generate, and share features through creation of a virtual feature store. You will abstract users from the physical architecture their models run on and make it easy for them to build high-quality models. You will build a feature marketplace so AI engineers can engineer features for all products at once rather than one at a time.Model AutomationCreate a common modeling workflow for all AI engineers with well-specified artifacts for feature engineering, feature analysis, model training, model analysis and more. You will move LinkedIn from bespoke machine learning approaches to industrialized machine learning. You will build automation to easy many of the common but time-consuming tasks in machine learning like neural architecture search and hyperparameter tuning.ProductionalizationMake it easy for AI engineers to safely deploy models and features in a uniform way across all LinkedIn products. You will build an end-to-end platform for streamlined feature generation, deployment, and serving, as well as easy model deployment and validation. You will rapidly increase iteration speed and decrease turnaround time for our AI engineers.The ideal candidate for this position will: Have experience building large scale data driven systems or platforms Have experience building or working with a machine learning platform Understand the fundamentals of machine learning, ideally in both academic and industry environments Be passionate about building simple, easy to use software systemsResponsibilities: Build and operate the platforms that power AI systems at LinkedIn. Enable a 24/7 production environment enabling AI researchers to iterate on robust, fault-tolerant, easy to use infrastructure. Provide high-quality internal technical support and documentation to make working with our infrastructure a delightful experience. Work closely with our technical leadership groups to drive and perform best engineering practices to initiate, plan, and execute large-scale, cross functional, and company-wise critical programs.Basic Qualifications: BA/BS Degree in Computer Science or related technical discipline, or related practical experience 3+ years experience in software design, development, and algorithm related solutions 3+ years experience programming in OOP languages like Java, Python, or C++Preferred Qualifications: BS and 4+ years of relevant work experience, MS and 2+ years of relevant work experience, or PhD and 1+ years of relevant work experience Experience in building machine learning platforms at large scale Familiarity with techniques used in big data and AI Good knowledge in distributed data processing technologies Experience with industry, open-source projects and/or academic research in large-data, machine learning systems, such as Spark, TensorFlow, PyTorch, or XGBoostEqual Opportunity StatementLinkedIn is committed to diversity in its workforce and is proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. LinkedIn is an Affirmative Action and Equal Opportunity Employer as described in our equal opportunity statement here: Please reference and for more information.LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful. If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at and describe the specific accommodation requested for a disability-related limitation. Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to: -Documents in alternate formats or read aloud to you -Having interviews in an accessible location-Being accompanied by a service dog-Having a sign language interpreter present for the interview A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response.LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information.Pay Transparency Policy StatementAs a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: Data Privacy Notice for Job CandidatesThis document provides transparency around the way in which LinkedIn handles personal data of employees and job applicants:

Keywords: LinkedIn, Sunnyvale , Senior Software Engineer - Machine Learning Infrastructure, IT / Software / Systems , Sunnyvale, California

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