onsite
MLOps / LLMOps Engineer - Bundesanzeiger Verlag
Software Engineer
Lead the design, deployment, and scaling of machine learning and large language model pipelines using Python, AWS, Docker, and Kubernetes, ensuring robust MLOps practices and continuous delivery.
About the role
Key Responsibilities
- Architect and maintain end‑to‑end ML/LLM pipelines from data ingestion to model serving.
- Implement CI/CD workflows with Git, Docker, and Kubernetes for automated model deployment.
- Integrate and optimize models on AWS services (SageMaker, ECS, EKS, Lambda).
- Monitor model performance, drift, and resource utilization; automate alerts and retraining triggers.
- Collaborate with data scientists, software engineers, and product teams to translate research into production‑ready solutions.
Requirements
- Strong experience in Python and ML frameworks (PyTorch, TensorFlow, Hugging Face).
- Proven track record in MLOps, including model versioning, reproducibility, and deployment at scale.
- Hands‑on expertise with AWS, Docker, and Kubernetes.
- Solid understanding of LLM architectures and fine‑tuning techniques.
- Excellent problem‑solving skills and ability to work in a fast‑paced, collaborative environment.
Skills
pythonmachine learningmlopsawsdockerkubernetes