Machine Learning Engineer

Tätigkeitsbereich:IT/TelekommunikationFachabteilung:Digital Customer ExperienceGesellschaft:Mercedes-Benz USA, LLCStandort:Mercedes-Benz USA, LLC Corporate Headquarters, Atlanta, GA Startdatum:sofortVeröffentlichungsdatum:06.11.2026Stellennummer:MER0004A3TArbeitszeit:VollzeitAufgabenAbout 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 Applied ML/AI Solutions Engineer is responsible for designing, building, anddelivering AI-powered solutions that drive measurable business value across Mercedes-Benz USA. This role develops copilots, intelligent assistants, agent-based solutions,and AI-enabled business processes that solve real-world business challenges.
The ideal candidate combines strong software engineering expertise, modern AIdevelopment experience, and solution architecture skills to deliver scalable, production-ready capabilities. This role works closely with data scientists, AI engineers, architects,and business stakeholders to transform opportunities into operational AI solutions.
ResponsibilitiesApplied AI Solution Delivery (60%)
• Design, develop, and deploy AI-powered applications, copilots, assistants, andagent-based solutions.
• Translate business requirements into scalable technical architectures andworking solutions.
• Integrate AI capabilities with enterprise applications, APIs, and operationalsystems.
• Deliver production-ready solutions that meet standards for performance,reliability, security, and supportability.
• Leverage established AI platform, LLMOps, and productization frameworks toaccelerate delivery.
• Contribute code, technical leadership, and best practices across the AI solutionportfolio.
Solution Architecture & Design (20%)
• Define solution architectures and technical designs for AI initiatives.
• Evaluate technologies, frameworks, and implementation approaches.
• Align solutions with enterprise architecture, security, and governance standards.
• Support planning, estimation, and technical execution activities.
Engineering Excellence & Innovation (10%)
• Establish and uphold standards for code quality, testing, documentation, andoperational readiness.
• Evaluate emerging AI technologies and development approaches.
• Contribute reusable patterns that improve delivery efficiency and consistency.
Collaboration & Technical Leadership (10%)
• Partner with business stakeholders, product teams, and engineering teams todrive successful outcomes.
• Mentor engineers and share expertise across the organization.
• Support knowledge sharing, cross-training, and team resilience initiatives.
Technical Skills & ToolsRequired
• Strong proficiency in Python and SQL.
• Experience developing and deploying production AI applications.
• Azure Databricks and cloud platforms such as Azure or AWS.
• Enterprise LLM platforms including Azure OpenAI, AWS Bedrock, or equivalent.
• Retrieval Augmented Generation (RAG) architectures and vector databases.
• REST APIs and modern integration practices.
• Software engineering best practices, testing, and CI/CD.
• Solution architecture and enterprise application integration experience.
Preferred
• LangChain, LangGraph, Semantic Kernel, Strands Agent SDK, or similarframeworks.
• React, TypeScript, Plotly Dash, Streamlit, or related technologies.
• Salesforce, ServiceNow, SAP, or Microsoft 365 integration experience.
• Agent orchestration frameworks and multi-agent architectures.
• Experience delivering AI use cases at enterprise scale. QualifikationenQualificationsRequiredBachelor's 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 AI/ML 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 ExperienceMaster's degree in Computer Science, Engineering, AI/ML, or related field.
Experience delivering enterprise-scale AI/ML 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 ac