Publicis Groupe Holdings B.V
Machine Learning Engineer, Manager
Publicis Groupe Holdings B.V, Birmingham, Michigan, us, 48012
Company description
Hi there! We're Razorfish. We've been leading the marketing industry with our digital expertise since the start of the internet. But in 2020, we did a full reboot. What's different? It all starts with people. Weird, wonderful, complex people - with diverse backgrounds in strategy, creative and technology. But no matter how different we are, we all have one thing in common. We believe our differences are our strength. So we push for inclusion, challenge convention and bring in new perspectives, to inspire new ideas. Because when we connect by understanding what makes people different, we can create unforgettable experiences that enrich lives. Join us at razorfish.com.
Overview
We're seeking a Machine Learning Engineer to help design, build, and maintain production-grade ML systems across cloud platforms. This role blends software engineering and ML expertise to translate prototypes into scalable solutions. You'll own the full ML lifecycle from development and deployment to monitoring and optimization using tools like Databricks, Vertex AI, and other cloud-native platforms. Strong technical skills, collaboration, and a passion for delivering AI at scale are essential.
Responsibilities
ML System Development & Deployment Design, build, and maintain scalable ML pipelines using cloud services (e.g., Vertex AI, Databricks, SageMaker, Azure ML) Develop and integrate microservices, REST APIs, and webhooks for ML model serving Implement CI/CD pipelines for automated model training, testing, and deployment Create robust data processing workflows for model training and inference MLOps & Infrastructure
Build and maintain ML infrastructure using modern MLOps practices and tools (e.g., MLflow, Kubeflow, Vertex AI Pipelines) Implement model monitoring, versioning, and performance tracking systems Design automated retraining pipelines and manage model lifecycle Ensure reliability, scalability, and security of models in production Optimize inference performance and cost efficiency across cloud platforms Software Engineering Excellence
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 Cross-Functional Collaboration
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 ML capabilities into customer-facing applications Participate in agile development processes and cross-functional project planning Provide technical guidance and mentorship to junior team members Qualifications
Education & Experience
Bachelor's degree in Computer Science, Software Engineering, Data Science, Mathematics, or related field 3-4 years of professional experience in ML engineering, software engineering, or data science 2+ years of hands-on experience deploying and maintaining ML models in production Experience working in collaborative, cross-functional team environments Technical Skills
Programming Languages : Strong proficiency in Python and SQL (2+ years) ML Frameworks : Experience with XGBoost, TensorFlow, PyTorch, sklearn, or Keras Cloud Platforms : Solid hands-on experience with GCP, AWS, or Azure ML Platforms : Practical knowledge of Vertex AI, SageMaker, Azure ML, or Databricks Analytics & Feature Engineering : Proficient with BigQuery, Redshift, Azure Synapse Distributed Processing : Skilled in Databricks, Apache Spark, Dataflow, Pub/Sub, Kafka Workflow Orchestration : Experience with Airflow, Cloud Composer, Jenkins Networking & Security : Understanding of cloud networking, security, and cost optimization MLOps & DevOps : Familiarity with CI/CD, ML lifecycle management API Development : Experience with REST APIs and microservices Version Control : Proficiency with Git and collaborative development workflows Core Competencies
Strong understanding of ML algorithms, model evaluation, and validation Experience with data preprocessing, feature engineering, and performance tuning Solid software engineering fundamentals and coding best practices Awareness of data privacy, security, and ethical AI principles Excellent collaboration skills with technical and non-technical stakeholders Self-driven learner with curiosity about emerging ML technologies Preferred Qualifications
Advanced Technical Skills
MLOps Tools: MLflow, Kubeflow, Vertex AI Pipelines Containerization: Docker; basic Kubernetes knowledge Specialized ML: Exposure to NLP, computer vision, or deep learning Modern ML: Familiarity with LLMs, RAG patterns, transformer architectures Professional Experience
Agile development and cross-functional collaboration Code review and technical documentation practices Interest in mentorship and knowledge sharing Experience with model validation and software testing principles Additional information
The Power of One starts with our people! To do powerful things, we offer powerful resources. Our best-in-class wellness and benefits offerings include:
Paid Family Care for parents and caregivers for 12 weeks or more Monetary assistance and support for Adoption, Surrogacy and Fertility Monetary assistance and support for pet adoption Employee Assistance Programs and Health/Wellness/Comfort reimbursements to help you invest in your future and work/life balance Tuition Assistance Paid time off that includes Flexible Time off Vacation, Annual Sick Days, Volunteer Days, Holiday and Identity days, and more Matching Gifts programs Flexible working arrangements 'Work Your World' Program encouraging employees to work from anywhere Publicis Groupe has an office for up to 6 weeks a year (based upon eligibility) Business Resource Groups that support multiple affinities and alliances
The benefits offerings listed are available to eligible U.S. Based employees, are reviewed on an annual basis, and are governed by the terms of the applicable plan documents.
Razorfish is an Equal Opportunity Employer. Our employment decisions are made without regard to actual or perceived race, color, ethnicity, religion, creed, sex, sexual orientation, gender, gender identity, gender expression, pregnancy, childbirth and related medical conditions, national origin, ancestry, citizenship status, age, disability, medical condition as defined by applicable state law, genetic information, marital status, military service and veteran status, or any other characteristic protected by applicable federal, state or local laws and ordinances.
If you require accommodation or assistance with the application or onboarding process specifically, please contact USMSTACompliance@publicis.com.
All your information will be kept confidential according to EEO guidelines.
Compensation Range: $87,210 to $119,300. This is the pay range the Company believes it will pay for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time. Temporary roles may be eligible to participate in our freelancer/temporary employee medical plan through a third-party benefits administration system once certain criteria have been met. Temporary roles may also qualify for participation in our 401(k) plan after eligibility criteria have been met. For regular roles, the Company will offer medical coverage, dental, vision, disability, 401k, and paid time off. The Company anticipates the application deadline for this job posting will be 9/1/25.
Hi there! We're Razorfish. We've been leading the marketing industry with our digital expertise since the start of the internet. But in 2020, we did a full reboot. What's different? It all starts with people. Weird, wonderful, complex people - with diverse backgrounds in strategy, creative and technology. But no matter how different we are, we all have one thing in common. We believe our differences are our strength. So we push for inclusion, challenge convention and bring in new perspectives, to inspire new ideas. Because when we connect by understanding what makes people different, we can create unforgettable experiences that enrich lives. Join us at razorfish.com.
Overview
We're seeking a Machine Learning Engineer to help design, build, and maintain production-grade ML systems across cloud platforms. This role blends software engineering and ML expertise to translate prototypes into scalable solutions. You'll own the full ML lifecycle from development and deployment to monitoring and optimization using tools like Databricks, Vertex AI, and other cloud-native platforms. Strong technical skills, collaboration, and a passion for delivering AI at scale are essential.
Responsibilities
ML System Development & Deployment Design, build, and maintain scalable ML pipelines using cloud services (e.g., Vertex AI, Databricks, SageMaker, Azure ML) Develop and integrate microservices, REST APIs, and webhooks for ML model serving Implement CI/CD pipelines for automated model training, testing, and deployment Create robust data processing workflows for model training and inference MLOps & Infrastructure
Build and maintain ML infrastructure using modern MLOps practices and tools (e.g., MLflow, Kubeflow, Vertex AI Pipelines) Implement model monitoring, versioning, and performance tracking systems Design automated retraining pipelines and manage model lifecycle Ensure reliability, scalability, and security of models in production Optimize inference performance and cost efficiency across cloud platforms Software Engineering Excellence
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 Cross-Functional Collaboration
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 ML capabilities into customer-facing applications Participate in agile development processes and cross-functional project planning Provide technical guidance and mentorship to junior team members Qualifications
Education & Experience
Bachelor's degree in Computer Science, Software Engineering, Data Science, Mathematics, or related field 3-4 years of professional experience in ML engineering, software engineering, or data science 2+ years of hands-on experience deploying and maintaining ML models in production Experience working in collaborative, cross-functional team environments Technical Skills
Programming Languages : Strong proficiency in Python and SQL (2+ years) ML Frameworks : Experience with XGBoost, TensorFlow, PyTorch, sklearn, or Keras Cloud Platforms : Solid hands-on experience with GCP, AWS, or Azure ML Platforms : Practical knowledge of Vertex AI, SageMaker, Azure ML, or Databricks Analytics & Feature Engineering : Proficient with BigQuery, Redshift, Azure Synapse Distributed Processing : Skilled in Databricks, Apache Spark, Dataflow, Pub/Sub, Kafka Workflow Orchestration : Experience with Airflow, Cloud Composer, Jenkins Networking & Security : Understanding of cloud networking, security, and cost optimization MLOps & DevOps : Familiarity with CI/CD, ML lifecycle management API Development : Experience with REST APIs and microservices Version Control : Proficiency with Git and collaborative development workflows Core Competencies
Strong understanding of ML algorithms, model evaluation, and validation Experience with data preprocessing, feature engineering, and performance tuning Solid software engineering fundamentals and coding best practices Awareness of data privacy, security, and ethical AI principles Excellent collaboration skills with technical and non-technical stakeholders Self-driven learner with curiosity about emerging ML technologies Preferred Qualifications
Advanced Technical Skills
MLOps Tools: MLflow, Kubeflow, Vertex AI Pipelines Containerization: Docker; basic Kubernetes knowledge Specialized ML: Exposure to NLP, computer vision, or deep learning Modern ML: Familiarity with LLMs, RAG patterns, transformer architectures Professional Experience
Agile development and cross-functional collaboration Code review and technical documentation practices Interest in mentorship and knowledge sharing Experience with model validation and software testing principles Additional information
The Power of One starts with our people! To do powerful things, we offer powerful resources. Our best-in-class wellness and benefits offerings include:
Paid Family Care for parents and caregivers for 12 weeks or more Monetary assistance and support for Adoption, Surrogacy and Fertility Monetary assistance and support for pet adoption Employee Assistance Programs and Health/Wellness/Comfort reimbursements to help you invest in your future and work/life balance Tuition Assistance Paid time off that includes Flexible Time off Vacation, Annual Sick Days, Volunteer Days, Holiday and Identity days, and more Matching Gifts programs Flexible working arrangements 'Work Your World' Program encouraging employees to work from anywhere Publicis Groupe has an office for up to 6 weeks a year (based upon eligibility) Business Resource Groups that support multiple affinities and alliances
The benefits offerings listed are available to eligible U.S. Based employees, are reviewed on an annual basis, and are governed by the terms of the applicable plan documents.
Razorfish is an Equal Opportunity Employer. Our employment decisions are made without regard to actual or perceived race, color, ethnicity, religion, creed, sex, sexual orientation, gender, gender identity, gender expression, pregnancy, childbirth and related medical conditions, national origin, ancestry, citizenship status, age, disability, medical condition as defined by applicable state law, genetic information, marital status, military service and veteran status, or any other characteristic protected by applicable federal, state or local laws and ordinances.
If you require accommodation or assistance with the application or onboarding process specifically, please contact USMSTACompliance@publicis.com.
All your information will be kept confidential according to EEO guidelines.
Compensation Range: $87,210 to $119,300. This is the pay range the Company believes it will pay for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time. Temporary roles may be eligible to participate in our freelancer/temporary employee medical plan through a third-party benefits administration system once certain criteria have been met. Temporary roles may also qualify for participation in our 401(k) plan after eligibility criteria have been met. For regular roles, the Company will offer medical coverage, dental, vision, disability, 401k, and paid time off. The Company anticipates the application deadline for this job posting will be 9/1/25.