AI/ML Platform Engineer

%3Cp style=%22font-family:Arial;%22%3E%3Cspan style=%22background-color:white;color:black;font-family:Calibri,sans-serif;font-size:10.0pt;%22%3E%3Cspan style=%22line-height:normal;%22%3E%3Cstrong%3EAbout Us%3C/strong%3E%3C/span%3E%3C/span%3E%3C/p%3E%3Cp style=%22font-family:Arial;%22%3E%3Cspan style=%22background-color:white;color:black;font-family:Calibri,sans-serif;font-size:10.0pt;%22%3E%3Cspan style=%22line-height:normal;%22%3EMercedes-Benz USA is responsible for the sales, marketing and service of all Mercedes-Benz and Maybach products in the United States.%26nbsp; In our people, you will find tremendous commitment to our corporate values: %27PRIDE = Passion, Respect, Integrity, Discipline, and Execution%27.%26nbsp; Our products and employees reflect this dedication.%26nbsp; We are looking for diverse top-notch individuals to join the Mercedes-Benz Team and uphold these hallmarks.%3C/span%3E%3C/span%3E%3C/p%3E%3Cp style=%22font-family:Arial;%22%3E%26nbsp;%3C/p%3E%3Cp style=%22font-family:Arial;%22%3E%3Cspan style=%22background-color:white;font-family:Calibri,sans-serif;font-size:10.0pt;%22%3E%3Cspan style=%22border:1.0pt none windowtext;line-height:15.0pt;padding:0in;vertical-align:baseline;%22%3E%3Cstrong%3EJob Overview%3C/strong%3E%3C/span%3E%3C/span%3E%3C/p%3E%3Cp%3EThe AI/ML 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 AI/ML 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.%3C/p%3E%3Cp%3EAs the platform foundation of the Applied AI Engineering %26amp; 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.%3Cbr%3E%26nbsp;%3C/p%3E%3Cp class=%22MsoNormal%22%3E%3Cstrong%3EResponsibilities%3C/strong%3E%3C/p%3E%3Cp class=%22MsoNormal%22%3E%3Cstrong%3EAI/ML Platform Engineering %26amp; Delivery (60%)%3C/strong%3E%3C/p%3E%3Cul style=%22margin-top:0in;%22 type=%22disc%22%3E%3Cli%3EDesign, build, and operate enterprise AI/ML platform capabilities and shared engineering services.%3C/li%3E%3Cli%3EDevelop and maintain model deployment pipelines, model registry capabilities, experiment tracking, and foundational MLOps tooling.%3C/li%3E%3Cli%3ECreate reusable platform components, templates, automation frameworks, and deployment standards that accelerate AI delivery.%3C/li%3E%3Cli%3EProvide the platform foundations supporting machine learning, generative AI, agent-based solutions, and AI productization initiatives.%3C/li%3E%3Cli%3EDesign and manage multi-tenancy patterns, resource isolation strategies, and workload governance across teams and business domains.%3C/li%3E%3Cli%3EEnsure platform reliability, scalability, security, observability, and cost optimization across AI workloads.%3C/li%3E%3Cli%3EDrive operational excellence through monitoring, incident response, resiliency improvements, and continuous platform enhancements.%3Cbr%3E%26nbsp;%3C/li%3E%3C/ul%3E%3Cp class=%22MsoNormal%22%3E%3Cstrong%3EPlatform Architecture %26amp; Engineering Standards (20%)%3C/strong%3E%3C/p%3E%3Cul%3E%3Cli%3EDefine and evolve platform architecture, deployment patterns, and engineering standards for AI/ML delivery.%3C/li%3E%3Cli%3EEvaluate emerging platform technologies and engineering approaches that improve scalability, performance, and developer productivity.%3C/li%3E%3Cli%3EPartner with architecture, infrastructure, security, and engineering teams to ensure alignment with enterprise standards.%3C/li%3E%3Cli%3EProvide technical leadership for platform investments, architecture decisions, and modernization initiatives.%3Cbr%3E%26nbsp;%3C/li%3E%3C/ul%3E%3Cp class=%22MsoNormal%22%3E%3Cstrong%3EOperational Excellence %26amp; Reliability (10%)%3C/strong%3E%3C/p%3E%3Cul%3E%3Cli%3EEstablish best practices for monitoring, logging, performance management, platform support, and operational readiness.%3C/li%3E%3Cli%3EDevelop engineering standards, documentation, automation, and operational runbooks.%3C/li%3E%3Cli%3EPromote continuous improvement of platform reliability, supportability, and operational maturity.%3Cbr%3E%26nbsp;%3C/li%3E%3C/ul%3E%3Cp class=%22MsoNormal%22%3E%3Cstrong%3ECollaboration %26amp; Technical Leadership (10%)%3C/strong%3E%3C/p%3E%3Cul%3E%3Cli%3ECollaborate with data scientists, AI engineers, architects, infrastructure teams, and business stakeholders.%3C/li%3E%3Cli%3EProvide technical mentorship and guidance across the AI Engineering organization.%3C/li%3E%3Cli%3ESupport knowledge sharing, cross-training, and engineering excellence initiatives.%3Cbr%3E%26nbsp;%3C/li%3E%3C/ul%3E%3Cp class=%22MsoNormal%22%3E%26nbsp;%3C/p%3E
%3Cp class=%22MsoNormal%22%3E%3Cstrong%3ETechnical Skills %26amp; Tools%3C/strong%3E%3C/p%3E%3Cp class=%22MsoNormal%22%3E%3Cstrong%3ERequired%3C/strong%3E%3C/p%3E%3Cul%3E%3Cli%3EStrong proficiency in Python, SQL, PySpark, and distributed data processing frameworks.%3C/li%3E%3Cli%3EExperience with Azure Databricks, including Unity Catalog, Delta Lake, MLflow, Feature Store, and Model Serving.%3C/li%3E%3Cli%3EExperience with Azure, AWS, or comparable cloud platforms supporting enterprise AI and machine learning workloads.%3C/li%3E%3Cli%3EExperience with model deployment pipelines, model registry management, experiment tracking, monitoring, and lifecycle management.%3C/li%3E%3Cli%3EExperience with CI/CD, workflow orchestration, and production AI platform operations.%3C/li%3E%3Cli%3EExperience with model serving, inference optimization, and scalable AI infrastructure.%3C/li%3E%3Cli%3EExperience with Docker, Kubernetes, Infrastructure as Code, and cloud-native deployment architectures.%3C/li%3E%3Cli%3EExperience supporting GPU-enabled workloads, distributed compute environments, and enterprise-scale platform operations.%3C/li%3E%3Cli%3EExperience with event-driven architectures, streaming technologies, and platform integration patterns.%3C/li%3E%3Cli%3EExperience with observability platforms, performance optimization, reliability engineering, and cloud cost management.%3C/li%3E%3Cli%3EStrong software engineering, automation, and production support practices.%3Cbr%3E%3Cbr%3E%26nbsp;%3C/li%3E%3C/ul%3E%3Cp class=%22MsoNormal%22%3E%3Cstrong%3EPreferred Skillset%3C/strong%3E%3C/p%3E%3Cul%3E%3Cli%3EExperience with Azure OpenAI, AWS Bedrock, or equivalent enterprise AI platforms.%3C/li%3E%3Cli%3EExperience with vector databases and retrieval technologies.%3C/li%3E%3Cli%3EExperience supporting generative AI and agent-based solutions at scale.%3C/li%3E%3Cli%3EFamiliarity with Responsible AI, AI governance, security, and risk management frameworks.%3Cbr%3E%26nbsp;%3C/li%3E%3C/ul%3E%3Cp class=%22MsoNormal%22%3E%3Cstrong%3EQualifications%3C/strong%3E%3C/p%3E%3Cp class=%22MsoNormal%22%3E%3Cstrong%3ERequired%3C/strong%3E%3C/p%3E%3Cul%3E%3Cli%3EBachelor%27s degree in Computer Science, Engineering, Data Science, Information Systems, or a related technical field.%3C/li%3E%3Cli%3E8+ years of experience in software engineering, machine learning engineering, AI platform engineering, or related disciplines.%3C/li%3E%3Cli%3EDemonstrated experience designing, building, and operating enterprise AI/ML platforms.%3C/li%3E%3Cli%3EStrong understanding of cloud-native architectures, MLOps, deployment automation, monitoring, and production operations.%3C/li%3E%3Cli%3EExperience building reusable engineering frameworks, platform services, or shared infrastructure capabilities.%3C/li%3E%3Cli%3EStrong communication, collaboration, and stakeholder management skills.%3Cbr%3E%26nbsp;%3C/li%3E%3C/ul%3E%3Cp class=%22MsoNormal%22%3E%3Cstrong%3EPreferred Experience%3C/strong%3E%3C/p%3E%3Cul%3E%3Cli%3EMaster%27s degree in Computer Science, Engineering, AI/ML, or related field.%3C/li%3E%3Cli%3EExperience delivering enterprise-scale AI/ML platforms supporting multiple business domains.%3C/li%3E%3Cli%3EExperience operating in regulated or compliance-sensitive environments.%3C/li%3E%3Cli%3EExperience scaling platform engineering capabilities supporting machine learning, generative AI, and agent-based systems.%3Cbr%3E%26nbsp;%3C/li%3E%3C/ul%3E%3Cp class=%22MsoNormal%22%3E%3Cstrong%3EAdditional Information%3C/strong%3E%3C/p%3E%3Cul%3E%3Cli%3EPosition requires regular collaboration with business, technology, and external partner teams across multiple time zones.%3C/li%3E%3Cli%3ESome travel required for team, partner, and business engagements.%3C/li%3E%3Cli%3EThis role is part of MBUSA%27s Data Insights %26amp; AI organization and contributes to the company%27s long-term AI strategy and operating model.%3C/li%3E%3C/ul%3E%3Cp class=%22MsoNormal%22 style=%22margin-left:.5in;%22%3E%26nbsp;%3C/p%3E%3Cp style=%22font-family:Arial;margin-bottom:11px;%22%3E%26nbsp;%3C/p%3E%3Cp style=%22font-family:Arial;margin-bottom:11px;%22%3E%3Cspan style=%22font-family:Calibri,sans-serif;font-size:10.0pt;%22%3E%3Cspan style=%22border:1.0pt none windowtext;line-height:107%;padding:0in;%22%3E%3Cstrong%3EEEO Statement%3C/strong%3E%3C/span%3E%3C/span%3E%3C/p%3E%3Cp style=%22font-family:Arial;%22%3E%3Cspan style=%22background-color:white;font-family:Calibri,sans-serif;font-size:10.0pt;%22%3E%3Cspan style=%22line-height:15.0pt;vertical-align:baseline;%22%3EMercedes-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.%3C/span%3E%3C/span%3E%3C/p%3E

Job Details
Group: Mercedes-Benz Group AG
Organization: Mercedes-Benz USA, LLC
Primary Location: United States of America-Georgia-Atlanta
Work Locations: One Mercedes-Benz Drive, Atlanta, 30328