LLMOps Engineer

Company Overview

At Daimler Truck, we change today’s transportation and create real impact together. We take responsibility around the globe and work together on making our vision become reality: Leading Sustainable Transportation. As one global team, we drive our progress and success together – everyone at Daimler Truck makes the difference. Together, we want to achieve sustainable transportation, reduce our carbon footprint, increase safety on and off the track, develop smarter technology, and attractive financial solutions. All essential to fulfill our purpose - for all who keep the world moving.

Job Summary

We are seeking a skilled and motivated LLMOps Engineer with 3-4 years of experience to join our Data & AI team. The ideal candidate will have hands-on experience in deploying, managing, and optimizing Large Language Models (LLMs) in production environments. This role requires a strong background in cloud infrastructure (Azure and AWS), MLOps practices, and DevOps tooling.

Responsibilities

• Design, build, and maintain scalable and secure LLM pipelines for training, fine-tuning, and inference.
• Automate deployment and monitoring of LLMs using CI/CD pipelines and Infrastructure-as-Code (IaC) tools.
• Optimize model performance and cost-efficiency across Azure and AWS environments.
• Collaborate with data scientists, ML engineers, and DevOps teams to ensure seamless integration of LLMs into applications.
• Implement observability and monitoring tools for model drift, latency, and performance metrics.
• Manage model versioning, rollback strategies, and reproducibility using tools like MLflow, DVC, or Weights & Biases.
• Build KPIs to manage LLM model performance, develop FinOps dashboard, and build I/O guardrails.
• Ensure compliance with data governance, security, and privacy standards in cloud environments.
• Evaluate and integrate third-party LLM APIs (e.g., OpenAI, Azure OpenAI, Anthropic) as needed.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 4–5 years of experience in MLOps, DevOps, or ML engineering roles.
• Strong hands-on experience with Azure (AKS, Azure ML, Azure OpenAI) and AWS (SageMaker, EKS, Lambda, S3).
• Proficiency in Python, Bash, and infrastructure-as-code tools (Terraform, Bicep, CloudFormation).
• Experience with containerization and orchestration (Docker, Kubernetes).
• Familiarity with LLM frameworks (Hugging Face Transformers, LangChain, DeepSpeed).
• Experience with CI/CD tools (GitHub Actions, Azure DevOps, Jenkins).
• Strong understanding of model lifecycle management and deployment best practices.
• Familiarity with LLMOps framework and prior knowledge on LibreChat.

Preferred Skills

• Strong experience in Statistics.
• Knowledge of ML/DL/Optimization and Generative AI.
• Background in Statistics, Econometrics, or related fields as part of the curriculum.

Experience

3-4 years of relevant experience in MLOps, DevOps, or ML engineering roles.

Environment

This role is situated in the Data & AI team and is likely to involve a hybrid work setup, encompassing both remote and in-office collaboration. The specific location details are not specified.

Salary

Not specified.

Growth Opportunities

The role presents opportunities for individual development through our own Learning Academy as well as free access to LinkedIn Learning.

Benefits

• Attractive compensation package.
• Company pension plan.
• Remote working and flexible working models.
• Health offers.
• Individual development opportunities.