{"schemaVersion":"jobsearcher.job.v1","id":"919122e742e2ce60e2fc1f16","url":"https://jobsearcher.com/jobs/919122e742e2ce60e2fc1f16","canonicalUrl":"https://jobsearcher.com/jobs/919122e742e2ce60e2fc1f16","title":"Manager, Data Engineering","description":"Company Description\r\nHi 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.\r\nOverview\r\nWe'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.\r\nFor this role, we expect the candidate to demonstrate a track record of:\r\nCollaborating with Data Science teams to deploy ML solutions into production.\r\nHands-on MLOps experience, including model deployment, monitoring, and lifecycle management.\r\nDesigning data warehouses and orchestrating data pipelines to support scalable ML operations.\r\nResponsibilities\r\nML System Development & Deployment\r\nDesign, build, and maintain scalable ML pipelines using cloud services (e.g., Vertex AI, Databricks, SageMaker, Azure ML)\r\nDevelop and integrate microservices, REST APIs, and webhooks for ML model serving\r\nImplement CI/CD pipelines for automated model training, testing, and deployment\r\nCreate robust data processing workflows for model training and inference\r\nMLOps & Infrastructure\r\nBuild and maintain ML infrastructure using modern MLOps practices and tools (e.g., MLflow, Kubeflow, Vertex AI Pipelines)\r\nImplement model monitoring, versioning, and performance tracking systems\r\nDesign automated retraining pipelines and manage model lifecycle\r\nEnsure reliability, scalability, and security of models in production\r\nOptimize inference performance and cost efficiency across cloud platforms\r\nSoftware Engineering Excellence\r\nWrite clean, maintainable, and well-documented code following best practices\r\nImplement comprehensive testing strategies including unit, integration, and model testing\r\nContribute to technical design reviews and architecture decisions\r\nMaintain high code quality standards and participate in code reviews\r\nCross-Functional Collaboration\r\nPartner with data scientists to productionize research models and prototypes\r\nCollaborate with data engineers to design efficient data pipelines and feature stores\r\nWork with product teams to integrate ML capabilities into customer-facing applications\r\nParticipate in agile development processes and cross-functional project planning\r\nProvide technical guidance and mentorship to junior team members\r\nQualifications\r\nEducation & Experience\r\nBachelor's degree in Computer Science, Software Engineering, Data Science, Mathematics, or related field\r\n3–4 years of professional experience in ML engineering, software engineering, or data science\r\n2+ years of hands-on experience deploying and maintaining ML models in production\r\nExperience working in collaborative, cross-functional team environments\r\nTechnical Skills\r\nProgramming Languages: Strong proficiency in Python and SQL (2+ years)\r\nML Frameworks: Experience with XGBoost, TensorFlow, PyTorch, sklearn, or Keras\r\nCloud Platforms: Solid hands-on experience with GCP, AWS, or Azure\r\nML Platforms: Practical knowledge of Vertex AI, SageMaker, Azure ML, or Databricks\r\nAnalytics & Feature Engineering: Proficient with BigQuery, Redshift, Azure Synapse\r\nDistributed Processing: Skilled in Databricks, Apache Spark, Dataflow, Pub/Sub, Kafka\r\nWorkflow Orchestration: Experience with Airflow, Cloud Composer, Jenkins\r\nNetworking & Security: Understanding of cloud networking, security, and cost optimization\r\nMLOps & DevOps: Familiarity with CI/CD, ML lifecycle management\r\nAPI Development: Experience with REST APIs and microservices\r\nVersion Control: Proficiency with Git and collaborative development workflows\r\nCore Competencies\r\nStrong understanding of ML algorithms, model evaluation, and validation\r\nExperience with data preprocessing, feature engineering, and performance tuning\r\nSolid software engineering fundamentals and coding best practices\r\nAwareness of data privacy, security, and ethical AI principles\r\nExcellent collaboration skills with technical and non-technical stakeholders\r\nSelf-driven learner with curiosity about emerging ML technologies\r\nPreferred Qualifications\r\nAdvanced Technical Skills\r\nMLOps Tools: MLflow, Kubeflow, Vertex AI Pipelines\r\nContainerization: Docker; basic Kubernetes knowledge\r\nSpecialized ML: Exposure to NLP, computer vision, or deep learning\r\nModern ML: Familiarity with LLMs, RAG patterns, transformer architectures\r\nProfessional Experience\r\nAgile development and cross-functional collaboration\r\nCode review and technical documentation practices\r\nInterest in mentorship and knowledge sharing\r\nExperience with model validation and software testing principles\r\nAdditional Information\r\nThe Power of One starts with our people! To do powerful things, we offer powerful resources.\r\nOur Best-in-class Wellness And Benefits Offerings Include\r\nPaid Family Care for parents and caregivers for 12 weeks or more\r\nMonetary assistance and support for Adoption, Surrogacy and Fertility\r\nMonetary assistance and support for pet adoption\r\nEmployee Assistance Programs and Health/Wellness/Comfort reimbursements to help you invest in your future and work/life balance\r\nTuition Assistance\r\nPaid time off that includes Flexible Time off Vacation, Annual Sick Days, Volunteer Days, Holiday and Identity days, and more\r\nMatching Gifts programs\r\nFlexible working arrangements\r\n'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)\r\nBusiness Resource Groups that support multiple affinities and alliances\r\nThe 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.\r\nRazorfish 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.\r\nIf you require accommodation or assistance with the application or onboarding process specifically, please contact USMSTACompliance@publicis.com.\r\nAll your information will be kept confidential according to EEO guidelines.\r\nCompensation Range: USD $88,540.00 - USD $121,100.00/Annually. 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 6/1/2026.\r\nJ-18808-Ljbffr","company":"Socket","rawCompany":"socket","city":"Birmingham","state":"MI","isRemote":false,"isActive":false,"createdAt":"2026-08-08T01:49:37.144Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Manager, Data Engineering","description":"Company Description\r\nHi 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.\r\nOverview\r\nWe'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.\r\nFor this role, we expect the candidate to demonstrate a track record of:\r\nCollaborating with Data Science teams to deploy ML solutions into production.\r\nHands-on MLOps experience, including model deployment, monitoring, and lifecycle management.\r\nDesigning data warehouses and orchestrating data pipelines to support scalable ML operations.\r\nResponsibilities\r\nML System Development & Deployment\r\nDesign, build, and maintain scalable ML pipelines using cloud services (e.g., Vertex AI, Databricks, SageMaker, Azure ML)\r\nDevelop and integrate microservices, REST APIs, and webhooks for ML model serving\r\nImplement CI/CD pipelines for automated model training, testing, and deployment\r\nCreate robust data processing workflows for model training and inference\r\nMLOps & Infrastructure\r\nBuild and maintain ML infrastructure using modern MLOps practices and tools (e.g., MLflow, Kubeflow, Vertex AI Pipelines)\r\nImplement model monitoring, versioning, and performance tracking systems\r\nDesign automated retraining pipelines and manage model lifecycle\r\nEnsure reliability, scalability, and security of models in production\r\nOptimize inference performance and cost efficiency across cloud platforms\r\nSoftware Engineering Excellence\r\nWrite clean, maintainable, and well-documented code following best practices\r\nImplement comprehensive testing strategies including unit, integration, and model testing\r\nContribute to technical design reviews and architecture decisions\r\nMaintain high code quality standards and participate in code reviews\r\nCross-Functional Collaboration\r\nPartner with data scientists to productionize research models and prototypes\r\nCollaborate with data engineers to design efficient data pipelines and feature stores\r\nWork with product teams to integrate ML capabilities into customer-facing applications\r\nParticipate in agile development processes and cross-functional project planning\r\nProvide technical guidance and mentorship to junior team members\r\nQualifications\r\nEducation & Experience\r\nBachelor's degree in Computer Science, Software Engineering, Data Science, Mathematics, or related field\r\n3–4 years of professional experience in ML engineering, software engineering, or data science\r\n2+ years of hands-on experience deploying and maintaining ML models in production\r\nExperience working in collaborative, cross-functional team environments\r\nTechnical Skills\r\nProgramming Languages: Strong proficiency in Python and SQL (2+ years)\r\nML Frameworks: Experience with XGBoost, TensorFlow, PyTorch, sklearn, or Keras\r\nCloud Platforms: Solid hands-on experience with GCP, AWS, or Azure\r\nML Platforms: Practical knowledge of Vertex AI, SageMaker, Azure ML, or Databricks\r\nAnalytics & Feature Engineering: Proficient with BigQuery, Redshift, Azure Synapse\r\nDistributed Processing: Skilled in Databricks, Apache Spark, Dataflow, Pub/Sub, Kafka\r\nWorkflow Orchestration: Experience with Airflow, Cloud Composer, Jenkins\r\nNetworking & Security: Understanding of cloud networking, security, and cost optimization\r\nMLOps & DevOps: Familiarity with CI/CD, ML lifecycle management\r\nAPI Development: Experience with REST APIs and microservices\r\nVersion Control: Proficiency with Git and collaborative development workflows\r\nCore Competencies\r\nStrong understanding of ML algorithms, model evaluation, and validation\r\nExperience with data preprocessing, feature engineering, and performance tuning\r\nSolid software engineering fundamentals and coding best practices\r\nAwareness of data privacy, security, and ethical AI principles\r\nExcellent collaboration skills with technical and non-technical stakeholders\r\nSelf-driven learner with curiosity about emerging ML technologies\r\nPreferred Qualifications\r\nAdvanced Technical Skills\r\nMLOps Tools: MLflow, Kubeflow, Vertex AI Pipelines\r\nContainerization: Docker; basic Kubernetes knowledge\r\nSpecialized ML: Exposure to NLP, computer vision, or deep learning\r\nModern ML: Familiarity with LLMs, RAG patterns, transformer architectures\r\nProfessional Experience\r\nAgile development and cross-functional collaboration\r\nCode review and technical documentation practices\r\nInterest in mentorship and knowledge sharing\r\nExperience with model validation and software testing principles\r\nAdditional Information\r\nThe Power of One starts with our people! To do powerful things, we offer powerful resources.\r\nOur Best-in-class Wellness And Benefits Offerings Include\r\nPaid Family Care for parents and caregivers for 12 weeks or more\r\nMonetary assistance and support for Adoption, Surrogacy and Fertility\r\nMonetary assistance and support for pet adoption\r\nEmployee Assistance Programs and Health/Wellness/Comfort reimbursements to help you invest in your future and work/life balance\r\nTuition Assistance\r\nPaid time off that includes Flexible Time off Vacation, Annual Sick Days, Volunteer Days, Holiday and Identity days, and more\r\nMatching Gifts programs\r\nFlexible working arrangements\r\n'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)\r\nBusiness Resource Groups that support multiple affinities and alliances\r\nThe 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.\r\nRazorfish 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.\r\nIf you require accommodation or assistance with the application or onboarding process specifically, please contact USMSTACompliance@publicis.com.\r\nAll your information will be kept confidential according to EEO guidelines.\r\nCompensation Range: USD $88,540.00 - USD $121,100.00/Annually. 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 6/1/2026.\r\nJ-18808-Ljbffr","datePosted":"2026-08-08T01:49:37.144Z","dateModified":"2026-08-08T01:49:37.144Z","hiringOrganization":{"@type":"Organization","name":"Socket","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Birmingham","addressRegion":"MI","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"919122e742e2ce60e2fc1f16"},"url":"https://jobsearcher.com/jobs/919122e742e2ce60e2fc1f16"}}