AI/ML Platform Engineer

Experteer Overview As an AI/ML Platform Engineer, you will build and operate enterprise AI/ML foundations that empower data scientists, AI engineers, and business teams to scale AI solutions. You’ll own reusable platform components, deployment pipelines, and lifecycle tooling across multi-tenant environments. You will work closely with cross-functional teams to ensure reliable, secure, and cost-efficient AI workloads. This role supports classical ML, generative AI, agent-based solutions, and analytics at scale, shaping Mercedes-Benz USA’s Applied AI Engineering & Operations capabilities. Compensation / Benefits * Design, build, and operate enterprise AI/ML platform capabilities and shared engineering services * Develop and maintain model deployment pipelines, model registry, and experiment tracking * Create reusable platform components, templates, automation frameworks, and deployment standards * Provide platform foundations for ML, generative AI, and AI productization initiatives * Design multi-tenancy, resource isolation, and workload governance across teams * Ensure platform reliability, security, observability, and cost optimization * Drive monitoring, incident response, resiliency, and continuous platform enhancements * Define and evolve platform architecture, deployment patterns, and engineering standards * Evaluate new platform technologies to improve scalability and developer productivity * Lead platform investments and modernization initiatives * Establish monitoring, logging, performance management, and operational runbooks * Foster knowledge sharing, cross-training, and engineering excellence initiatives * Collaborate with data scientists, AI engineers, architects, and stakeholders * Provide technical mentorship across the AI Engineering organization Tasks * Bachelor’s degree in a technical field * 8+ years of software or AI platform engineering experience * Proven ability to design, build, and operate enterprise AI/ML platforms * Strong understanding of cloud-native architectures, MLOps, deployment automation, monitoring, and production operations * Experience building reusable engineering frameworks or shared infrastructure Key requirements *

USA’s multi-tenancy, resource isolation, and workload governance across teams * Ensure platform reliability, security, observability, and cost optimization * Drive monitoring, incident response, resiliency, and continuous platform enhancements * Define and evolve platform architecture, deployment patterns, and engineering standards * Evaluate new platform technologies to improve scalability and developer productivity * Lead platform investments and modernization initiatives * Establish monitoring, logging, performance management, and operational runbooks * Foster knowledge sharing, cross-training, and engineering excellence initiatives * Collaborate with data scientists, AI engineers, architects, and stakeholders * Provide technical mentorship across the AI Engineering organization Tasks * Bachelor’s degree in a technical field * 8+ years of software or AI platform engineering experience * Proven ability to design, build, and operate enterprise AI/ML platforms * Strong understanding of cloud-native architectures, MLOps, deployment automation, monitoring, and production operations * Experience building reusable engineering frameworks or shared infrastructure Key requirements *