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Daimler Truck North America
Daimler Truck North America
H1B Visa SponsorAutomotiveLogisticsTransport
Daimler Truck North America develops and delivers vehicles, technologies, and services for the commercial transportation industry. Its portfolio includes medium- and heavy-duty trucks, school buses, chassis, and related transportation solutions associated with Freightliner, Western Star, and Thomas Built Buses. The company brings together engineering, manufacturing, marketing, and service expertise, with a focus on advancing innovation and sustainability across logistics, automotive, and transport.
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Data Science Supervisor II

Lead AI architecture, retrieval-augmented generation (RAG) agents, and scalable data platforms at Daimler Truck North America. Guide teams building governed AI solutions for manufacturing, finance, and aftermarket operations.

USUnited StatesOROregonHybridFull-timeSeniorLeadEnglish RequiredData Scientist
AWSAzureCloudETLKafkaSQL

Description

  • Develop data and AI products using DTNA and Daimler Truck data foundations and emerging technologies.
  • Lead data architecture, AI implementation, and collaboration across regions.
  • Review architectures and advise on technical direction, feasibility, and scalability for AI initiatives.
  • Find high-impact data and AI opportunities across business units and regions.
  • Coordinate with DTG data leads, architects, and group technical leaders on data and AI solutions.
  • Work with DTICI to establish global data and AI architecture standards and solutions.
  • Adapt global data and AI solutions to regional needs and regulatory requirements.
  • Build internal knowledge sharing through data and AI communities of practice.
  • Keep the enterprise data platform scalable and ready for AI, with discoverable, governed, usable data.
  • Partner with business leaders to select valuable use cases and develop proofs of concept and minimum viable products.
  • Assess and pilot AI tools, platforms, models, and vendors, and recommend architecture roadmaps.
  • Use AI to improve data preparation, quality, documentation, and automation.
  • Create patterns, pipelines, and MLOps and LLMOps practices to deploy and scale AI solutions.
  • Apply responsible AI practices that meet security, privacy, quality, and governance standards.
  • Advise stakeholders on AI capabilities and help them build relevant skills and prioritize work.
  • Lead the design and hands-on delivery of enterprise RAG and agent-based solutions.
  • Build enterprise AI agents with RAG, semantic retrieval, vector search, tool orchestration, and multi-agent workflows.
  • Set AI quality measures and evaluation frameworks, including reference datasets, pipelines, LLM-as-judge processes, and regression tests.
  • Create semantic and ontology-based data models for enterprise AI, self-service analytics, reasoning, and knowledge discovery.
  • Assess and adopt emerging AI standards, including the Model Context Protocol (MCP).
  • Manage a team of AI and data professionals.
  • Conduct employee reviews and impact discussions, and provide feedback and guidance.
  • Support development plans and recruit, mentor, and retain AI talent.
  • Build a collaborative and inclusive team culture.
  • Set team goals and performance targets that support strategic priorities.
  • Develop high-performing engineering teams through hiring, technical interviews, mentoring, and talent development.
  • Provide technical leadership through architecture, design, code, AI solution, and production-readiness reviews.

Requirements

  • Bachelor’s degree in a technical or design discipline such as computer science, software design, or data science, plus at least seven years of relevant experience.
  • Experience with major cloud analytics platforms.
  • Experience with major big data analytics platforms.
  • Experience with generative AI and leading large language models.
  • Experience deploying and managing large cloud compute workloads for performance and cost efficiency.
  • Expert-level SQL skills.
  • Extensive hands-on experience with conceptual, logical, and physical data modeling and relational and non-relational data stores.
  • Strong understanding of data engineering and architecture.
  • Demonstrated experience designing and operating ETL/ELT pipelines and modern data platforms.
  • Experience preparing and architecting data for machine learning and AI use.
  • Ability to work with structured and unstructured data at scale.
  • Experience with streaming and real-time data architectures, including Kafka and event-driven pipelines.
  • Experience with distributed computing frameworks.
  • Experience with cloud-native AI services such as Azure AI and AWS SageMaker.
  • Experience with containerization and orchestration.
  • Hands-on experience with agentic AI frameworks or orchestration tools and major AI and data platform ecosystems.
  • Experience taking AI solutions from prototype to reliable, monitored production at scale.
  • Track record of delivering business transformation through data and AI.
  • Strong business judgment and ability to explain complex technical topics to non-technical audiences.
  • Experience in multinational or matrixed organizations.
  • A resume must be attached to the application.
  • The selected candidate must pass a criminal background check.
  • The selected candidate may be required to pass a pre-employment drug screen.
  • Applicants must be authorized to work permanently in the United States when applying, except current Daimler Truck North America employees working under an existing U.S. Daimler Truck North America visa.
  • An advanced degree in computer science, AI, data science, or a related field is preferred.
  • Experience with large datasets and distributed computing is a plus.
  • Experience using GitHub or a similar collaborative development platform is a plus.
  • Experience with manufacturing, finance, or aftermarket data is a plus.
  • Familiarity with regional regulatory frameworks and data privacy laws is a plus.
  • Multilingual skills or experience working across diverse cultures is a plus.
  • Thought leadership demonstrated through publications or speaking engagements is a plus.

Benefits

  • Relocation assistance is not offered for this position.
  • Hybrid schedule with four days in the office and one remote day per week.
  • Equal employment opportunity; accommodation or special assistance is available during the application process.
  • The hiring process may include a pre-employment drug screen and criminal background check.

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