Machine Learning Engineer I

Condé Nast is seeking a motivated and skilled Machine Learning Engineer I to support the productionization of machine learning projects within Databricks or AWS environments for the Data Science team. This role is crucial for transforming data science prototypes into scalable, reliable production pipelines. The engineer will be responsible for building, optimizing, and maintaining data and ML pipelines, contributing to the design and implementation of scalable ML workflows, and supporting near-real-time and batch processing systems. Collaboration with Machine Learning Engineers and Data Scientists is key, focusing on deploying, optimizing, and operating ML models rather than building new ones.

Must Have

• Build, optimize, and maintain data and ML pipelines.
• Assist in transforming data science prototypes into reusable, production-ready engineering frameworks.
• Contribute to the design and implementation of scalable ML workflows processing large volumes of data.
• Support near-real-time and batch processing systems for ML use cases.
• Collaborate closely with Machine Learning Engineers and Data Scientists in designing and engineering ML solutions.
• Participate in the full development lifecycle, from design and implementation to testing and release.
• Implement and maintain CI/CD pipelines for ML models and data workflows.
• Proactively identify, debug, and resolve issues in ML pipelines and production jobs.
• Follow agile development practices with a focus on code quality, testing, and incremental delivery.
• Participate in quality assurance, testing, and defect resolution.
• Strong proficiency in Python, with experience using libraries such as TensorFlow, PyTorch, scikit-learn, Pandas, NumPy, and PySpark.
• Good understanding of data structures, data modeling, and software engineering principles.
• Experience working with big data technologies such as Spark, Hadoop, Kafka, Hive, or AWS EMR.
• Exposure to Databricks or Amazon SageMaker for ML development or deployment.
• Experience building data pipelines and ML workflows in production or pre-production environments.
• Familiarity with API development and serving ML models as RESTful services.
• Experience working with Docker and basic exposure to Kubernetes is a plus.
• Experience with CI/CD pipelines for ML or data workflows.

Good to Have

• Experience using Airflow, Astronomer, MLflow, or Kubeflow.
• Exposure to Spark, or PySpark in data processing systems.
• Familiarity with AWS services commonly used in ML pipelines (S3, EC2, IAM, etc.).
• Experience with near-real-time data processing use cases.

Job Description

About The Role:

Condé Nast is seeking a motivated and skilled Machine Learning Engineer I to support the productionization of machine learning projects in Databricks or AWS environments for the Data Science team.

This role is ideal for an engineer with a strong foundation in software development, data engineering, and machine learning, who enjoys transforming data science prototypes into scalable, reliable production pipelines.

Note: This role focuses on deploying, optimizing, and operating ML models rather than building or researching new machine learning models.

Primary Responsibilities

• Build, optimize, and maintain data and ML pipelines to deploy machine learning models into production environments.
• Assist in transforming data science prototypes into reusable, production-ready engineering frameworks.
• Contribute to the design and implementation of scalable ML workflows processing large volumes of data.
• Support near-real-time and batch processing systems for ML use cases.
• Collaborate closely with Machine Learning Engineers and Data Scientists in designing and engineering ML solutions.
• Participate in the full development lifecycle, from design and implementation to testing and release.
• Implement and maintain CI/CD pipelines for ML models and data workflows.
• Proactively identify, debug, and resolve issues in ML pipelines and production jobs.
• Follow agile development practices with a focus on code quality, testing, and incremental delivery.
• Participate in quality assurance, testing, and defect resolution.

Desired Skills & Qualifications

• 2-4 years of software development experience involving machine learning or data-intensive systems.
• Strong proficiency in Python, with experience using libraries such as TensorFlow, PyTorch, scikit-learn, Pandas, NumPy, and PySpark.
• Good understanding of data structures, data modeling, and software engineering principles.
• Experience working with big data technologies such as Spark, Hadoop, Kafka, Hive, or AWS EMR.
• Exposure to Databricks or Amazon SageMaker for ML development or deployment.
• Experience building data pipelines and ML workflows in production or pre-production environments.
• Familiarity with API development and serving ML models as RESTful services.
• Experience working with Docker and basic exposure to Kubernetes is a plus.
• Experience with CI/CD pipelines for ML or data workflows.
• Good communication skills and ability to work effectively within a team.
• Strong analytical and problem-solving skills.
• Undergraduate or Postgraduate degree in Computer Science or a related discipline.

Preferred Qualifications

• Experience using Airflow, Astronomer, MLflow, or Kubeflow.
• Exposure to Spark, or PySpark in data processing systems.
• Familiarity with AWS services commonly used in ML pipelines (S3, EC2, IAM, etc.).
• Experience with near-real-time data processing use cases.

What happens next?

If you are interested in this opportunity, please apply below, and we will review your application as soon as possible. You can update your resume or upload a cover letter at any time by accessing your candidate profile.

Condé Nast is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, age, familial status and other legally protected characteristics.

About Us

Condé Nast is a global media company home to iconic brands including Vogue, GQ, AD, Condé Nast Traveler, Vanity Fair, Wired, The New Yorker, Glamour, Allure, Bon Appétit, Self and many more. Headquartered in New York and London, the company produces award-winning journalism, content and entertainment for every platform today and operates in 32 markets worldwide including China, France, Germany, India, Italy, Japan, Mexico, Spain, the U.K. and U.S., and Taiwan.

At Condé Nast we value diversity of background, views and cultures. We celebrate people for their personal qualities, their skills and contributions. And we recognize the power our brands have to influence and shape culture, catalyze action and help make our world a better place for all.

For more information, please visit condenast.com and follow @CondeNast and @CondeNastCareer for Twitter and @condenastcareers for Instagram.

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