


Job Summary
Condé Nast is seeking an experienced and highly motivated Software engineer-ML who will support
productionizing projects in a databricks environment for the data science team. We expect the person
to be a software/data engineer experienced in building robust ML systems & deploying ML pipelines
in production, Study and transform data science prototypes into an engineering product and is
knowledgeable about machine learning models.
**This role is NOT for building Machine Learning models **
Primary Responsibilities
● Operationalize ML models into production environment(s) by building data
pipelines ● Designing and developing Machine Learning Systems
● Keep abreast of developments in the field
● Come up with engineering ideas to resolve problems faced with respect to ML pipeline ●
Design and code highly scalable, machine learning frameworks processing large volumes of data
● Engineer a near-real-time system that can process massive amounts of data efficiently ●
Collaborate with other Machine Learning Engineers and Data Scientists in architecting &
engineering the solution
● Participate in the entire development lifecycle, from concept to release
● Participate in all phases of quality assurance and defect resolution
Desired Skills & Qualifications
● 5+ years software development experience with highly scalable systems involving
machine learning and big data
● Understanding of data structures, data modeling and software architecture
● Strong software development skills with proficiency in Python/Pyspark
● Experience with Big Data technologies such as Spark, Hadoop
● Familiarity with machine learning frameworks and libraries would be a good-to-have
skill ● Excellent communication skills
● Ability to work in a team
● Outstanding analytical and problem-solving skills
● Applicants should have a Undergraduate/Postgraduate degree in Computer Science or a
related discipline
About Condé Nast
CONDÉ NAST GLOBAL
Condé Nast is a global media house with over a century of distinguished publishing history. With a
portfolio of iconic brands like Vogue, GQ, Vanity Fair, The New Yorker and Bon Appétit, we at Condé Nast
aim to tell powerful, compelling stories of communities, culture and the contemporary world. Our
operations are headquartered in New York and London, with colleagues and collaborators in 32 markets
across the world, including France, Germany, India, China, Japan, Spain, Italy, Russia, Mexico, and Latin
America.
Condé Nast has been raising the industry standards and setting records for excellence in the publishing
space. Today, our brands reach over 1 billion people in print, online, video, and social media.
CONDÉ NAST INDIA (DATA)
Over the years, Condé Nast successfully expanded and diversified into digital, TV, and social platforms -
in other words, a staggering amount of user data. Condé Nast made the right move to invest heavily in
understanding this data and formed a whole new Data team entirely dedicated to data processing,
engineering, analytics, and visualization. This team helps drive engagement, fuel process innovation,
further content enrichment, and increase market revenue. The Data team aimed to create a company
culture where data was the common language and facilitate an environment where insights shared in
real-time could improve performance.
The Global Data team operates out of Los Angeles, New York, Chennai, and London. The team at Condé
Nast Chennai works extensively with data to amplify its brands' digital capabilities and boost online
revenue. We are broadly divided into four groups, Data Intelligence, Data Engineering, Data Science, and
Operations (including Product and Marketing Ops, Client Services) along with Data Strategy and
monetization. The teams-built capabilities and products to create data-driven solutions for better
audience engagement.
What we look forward to:
We want to welcome bright, new minds into our midst and work together to create diverse forms of
self-expression. At Condé Nast, we encourage the imaginative and celebrate the extraordinary. We are a
media company for the future, with a remarkable past. We are Condé Nast, and It Starts Here.

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