AIML Platform Engineer

Aufgaben About UsMercedes-Benz USA is responsible for the sales marketing and service of all Mercedes-Benz and Maybach products in the United States. In our people you will find tremendous commitment to our corporate values PRIDE Passion Respect Integrity Discipline and Execution. Our products and employees reflect this dedication. We are looking for diverse top-notch individuals to join the Mercedes-Benz Team and uphold these hallmarks.Job OverviewThe AIML Platform Engineer is responsible for the foundational platform capabilities that power AI and machine learning delivery across Mercedes-Benz USA. This role designs builds and operates shared AIML infrastructure deployment pipelines model lifecycle tooling and reusable engineering services that enable data scientists AI engineers and business teams to develop and scale AI solutions efficiently.As the platform foundation of the Applied AI Engineering & Operations team this role supports classical machine learning generative AI agent-based solutions and enterprise-scale analytics workloads. The ideal candidate combines strong platform engineering expertise cloud experience MLOps knowledge and production operations experience with a passion for building reliable and scalable engineering foundations.ResponsibilitiesAIML Platform Engineering & Delivery 60Design build and operate enterprise AIML platform capabilities and shared engineering services.Develop and maintain model deployment pipelines model registry capabilities experiment tracking and foundational MLOps tooling.Create reusable platform components templates automation frameworks and deployment standards that accelerate AI delivery.Provide the platform foundations supporting machine learning generative AI agent-based solutions and AI productization initiatives.Design and manage multi-tenancy patterns resource isolation strategies and workload governance across teams and business domains.Ensure platform reliability scalability security observability and cost optimization across AI workloads.Drive operational excellence through monitoring incident response resiliency improvements and continuous platform enhancements.Platform Architecture & Engineering Standards 20Define and evolve platform architecture deployment patterns and engineering standards for AIML delivery.Evaluate emerging platform technologies and engineering approaches that improve scalability performance and developer productivity.Partner with architecture infrastructure security and engineering teams to ensure alignment with enterprise standards.Provide technical leadership for platform investments architecture decisions and modernization initiatives.Operational Excellence & Reliability 10Establish best practices for monitoring logging performance management platform support and operational readiness.Develop engineering standards documentation automation and operational runbooks.Promote continuous improvement of platform reliability supportability and operational maturity.Collaboration & Technical Leadership 10Collaborate with data scientists AI engineers architects infrastructure teams and business stakeholders.Provide technical mentorship and guidance across the AI Engineering organization.Support knowledge sharing cross-training and engineering excellence initiatives. Qualifikationen Technical Skills & ToolsRequiredStrong proficiency in Python SQL PySpark and distributed data processing frameworks.Experience with Azure Databricks including Unity Catalog Delta Lake MLflow Feature Store and Model Serving.Experience with Azure AWS or comparable cloud platforms supporting enterprise AI and machine learning workloads.Experience with model deployment pipelines model registry management experiment tracking monitoring and lifecycle management.Experience with CICD workflow orchestration and production AI platform operations.Experience with model serving inference optimization and scalable AI infrastructure.Experience with Docker Kubernetes Infrastructure as Code and cloud-native deployment architectures.Experience supporting GPU-enabled workloads distributed compute environments and enterprise-scale platform operations.Experience with event-driven architectures streaming technologies and platform integration patterns.Experience with observability platforms performance optimization reliability engineering and cloud cost management.Strong software engineering automation and production support practices.Preferred SkillsetExperience with Azure OpenAI AWS Bedrock or equivalent enterprise AI platforms.Experience with vector databases and retrieval technologies.Experience supporting generative AI and agent-based solutions at scale.Familiarity with Responsible AI AI governance security and risk management frameworks.QualificationsRequiredBachelors degree in Computer Science Engineering Data Science Information Systems or a related technical field.8 years of experience in software engineering machine learning engineering AI platform engineering or related disciplines.Demonstrated experience designing building and operating enterprise AIML platforms.Strong understanding of cloud-native architectures MLOps deployment automation monitoring and production operations.Experience building reusable engineering frameworks platform services or shared infrastructure capabilities.Strong communication collaboration and stakeholder management skills.Preferred ExperienceMasters degree in Computer Science Engineering AIML or related field.Experience delivering enterprise-scale AIML platforms supporting multiple business domains.Experience operating in regulated or compliance-sensitive environments.Experience scaling platform engineering capabilities supporting machine learning generative AI and agent-based systems.Additional InformationPosition requires regular collaboration with business technology and external partner teams across multiple time zones.Some travel required for team partner and business engagements.This role is part of MBUSAs Data Insights & AI organization and contributes to the companys long-term AI strategy and operating model.EEO StatementMercedes-Benz USA is committed to fostering an inclusive environment that appreciates and leverages the diversity of our team. We provide equal employment opportunity EEO to all qualified applicants and employees without regard to race color ethnicity gender age national origin religion marital status veteran status physical or other disability sexual orientation gender identity or expression or any other characteristic protected by federal state or local law.

solutions and enterprise-scale analytics workloads. The ideal candidate combines strong platform engineering expertise cloud experience MLOps knowledge and production operations experience with a passion for building reliable and scalable engineering foundations.ResponsibilitiesAIML Platform Engineering & Delivery 60Design build and operate enterprise AIML platform capabilities and shared engineering services.Develop and maintain model deployment pipelines model registry capabilities experiment tracking and foundational MLOps tooling.Create reusable platform components templates automation frameworks and deployment standards that accelerate AI delivery.Provide the platform foundations supporting machine learning generative AI agent-based solutions and AI productization initiatives.Design and manage multi-tenancy patterns resource isolation strategies and workload governance across teams and business domains.Ensure platform reliability scalability security observability and cost, maturity.Collaboration & Technical Leadership 10Collaborate with data scientists AI engineers architects infrastructure teams and business stakeholders.Provide technical mentorship and guidance across the AI Engineering organization.Support knowledge sharing cross-training and engineering excellence initiatives. Qualifikationen Technical Skills & ToolsRequiredStrong proficiency in Python SQL PySpark and distributed data processing frameworks.Experience with Azure Databricks including Unity Catalog Delta Lake MLflow Feature Store and Model Serving.Experience with Azure AWS or comparable cloud platforms supporting enterprise AI and machine learning workloads.Experience with model deployment pipelines model registry management experiment tracking monitoring and lifecycle management.Experience with CICD workflow orchestration and production AI platform operations.Experience with model serving inference optimization and scalable AI infrastructure.Experience with Docker Kubernetes, engineering or related disciplines, Demonstrated experience designing building and operating enterprise AIML platforms.Strong understanding of cloud-native architectures MLOps deployment automation monitoring and production operations.Experience building reusable engineering frameworks platform services or shared infrastructure capabilities.Strong communication collaboration and stakeholder management skills.Preferred ExperienceMasters degree in Computer Science Engineering AIML or related field.Experience delivering enterprise-scale AIML platforms supporting multiple business domains.Experience operating in regulated or compliance-sensitive environments.Experience scaling platform engineering capabilities supporting machine learning generative AI and agent-based systems.Additional InformationPosition requires regular collaboration with business technology and external partner teams across multiple time zones.Some travel required for team partner and business engagements.This role is part of

Aufgaben About UsMercedes-Benz USA is responsible for the sales marketing and service of all Mercedes-Benz and Maybach products in the United States. In our people you will find tremendous commitment to our corporate values PRIDE Passion Respect Integrity Discipline and Execution. Our products and employees reflect this dedication. We are looking for diverse top-notch individuals to join the Mercedes-Benz Team and uphold these hallmarks.Job OverviewThe AIML Platform Engineer is responsible for the foundational platform capabilities that power AI and machine learning delivery across Mercedes-Benz USA. This role designs builds and operates shared AIML infrastructure deployment pipelines model lifecycle tooling and reusable engineering services that enable data scientists AI engineers and business teams to develop and scale AI solutions efficiently.As the platform foundation of the Applied AI Engineering & Operations team this role supports classical machine learning generative AI agent-based, MBUSAs Data Insights & AI organization and contributes to the companys long-term AI strategy and operating model.EEO StatementMercedes-Benz USA is committed to fostering an inclusive environment that appreciates and leverages the diversity of our team. We provide equal employment opportunity EEO to all qualified applicants and employees without regard to race color ethnicity gender age national origin religion marital status veteran status physical or other disability sexual orientation gender identity or expression or any other characteristic protected by federal state or local law.