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Publicis Groupe

Runs advertising and digital transformation services

Machine Learning Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeBirmingham, MI, USA$87.2k - $119.3k /yrIn-person

About the Job

Requirements

  • A bachelor's degree in Computer Science, Software Engineering, Data Science, Mathematics, or a related field is required.
  • Three to four years of professional experience in machine learning engineering, software engineering, or data science is required.
  • At least two years of hands-on experience deploying and maintaining machine learning models in production is required.
  • Experience working in collaborative, cross-functional team environments is required.
  • Strong proficiency in Python and SQL, with at least two years of experience, is required.
  • Experience with XGBoost, TensorFlow, PyTorch, scikit-learn, or Keras is required.
  • Hands-on experience with GCP, AWS, or Azure is required.
  • Practical knowledge of Vertex AI, SageMaker, Azure ML, or Databricks is required.
  • Proficiency with BigQuery, Redshift, or Azure Synapse is required.
  • Skill with Databricks, Apache Spark, Dataflow, Pub/Sub, or Kafka is required.
  • Experience with Airflow, Cloud Composer, or Jenkins is required.
  • Understanding of cloud networking, security, and cost optimization is required.
  • Familiarity with CI/CD and machine learning lifecycle management is required.
  • Experience with REST APIs and microservices is required.
  • Proficiency with Git and collaborative development workflows is required.
  • A strong understanding of machine learning algorithms, model evaluation, and validation is required.
  • Experience with data preprocessing, feature engineering, and performance tuning is required.
  • Solid software engineering fundamentals and coding best practices are required.
  • Awareness of data privacy, security, and ethical AI principles is required.

Responsibilities

  • Design, build, and maintain scalable machine learning pipelines using cloud services such as Vertex AI, Databricks, SageMaker, or Azure ML.
  • Develop and integrate microservices, REST APIs, and webhooks for machine learning model serving.
  • Implement CI/CD pipelines for automated model training, testing, and deployment.
  • Create robust data-processing workflows for model training and inference.
  • Build and maintain machine learning infrastructure using MLOps practices and tools such as MLflow, Kubeflow, and Vertex AI Pipelines.
  • Implement model monitoring, versioning, and performance-tracking systems.
  • Design automated retraining pipelines and manage model lifecycle.
  • Ensure the reliability, scalability, and security of models in production.
  • Optimize inference performance and cost efficiency across cloud platforms.
  • Write clean, maintainable, and well-documented code following best practices.
  • Implement comprehensive testing strategies, including unit, integration, and model testing.
  • Contribute to technical design reviews and architecture decisions.
  • Maintain high code-quality standards and participate in code reviews.
  • Partner with data scientists to productionize research models and prototypes.
  • Collaborate with data engineers to design efficient data pipelines and feature stores.
  • Work with product teams to integrate machine learning capabilities into customer-facing applications.
  • Participate in agile development processes and cross-functional project planning.
  • Provide technical guidance and mentorship to junior team members.

Desired Qualifications

  • Knowledge of MLOps tools such as MLflow, Kubeflow, and Vertex AI Pipelines is preferred.
  • Experience with Docker and basic Kubernetes knowledge is preferred.
  • Exposure to natural language processing, computer vision, or deep learning is preferred.
  • Familiarity with large language models, retrieval-augmented generation patterns, and transformer architectures is preferred.
  • Experience with agile development and cross-functional collaboration is preferred.
  • Experience with code review and technical documentation practices is preferred.
  • Interest in mentorship and knowledge sharing is preferred.
  • Experience with model validation and software testing principles is preferred.

About the Company

Publicis Groupe

Runs advertising and digital transformation services

Publicis Groupe runs advertising, media buying and digital transformation services for companies that want to reach consumers, coordinate campaigns and improve their business systems. Its agency network includes creative and media specialists, while Publicis Sapient builds and modernizes the technology behind clients' operations. Epsilon adds customer data and marketing technology that connect brands with audiences and measure campaign results. Clients pay for consulting, campaign creation and execution, with production and media costs billed through alongside the group's service work. Founded in 1926, Publicis Groupe is headquartered in Paris, France.

Company size
10,001+
Company stage
IPO
Headquarters
Paris, France
Founded
1926

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