Senior Software Engineer - Machine Learning Infrastructure
Company: LinkedIn
Location: Sunnyvale
Posted on: February 20, 2021
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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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