AI Engineer for Cloud Engineering and MLOps
il y a 4 jours
Job Overview
We are looking for an experienced MLOps/LLMOps specialist with a strong background in cloud engineering to elevate our technological capabilities.
Main Responsibilities
- Deploy and serve fine-tuned open-source large language models and automatic speech recognition models.
- Utilize Kubernetes and Docker to optimize the deployment and management of ML models, ensuring efficient use of GPU resources.
- Build and maintain robust infrastructure on Azure, leveraging automation tools such as Terraform and Bicep for efficient resource management and deployment.
- Implement continuous observability, monitoring and A/B testing strategies to evaluate and enhance LLM & ASR model's performance and reliability.
Required Skills
- In-depth experience with MLFlow, Databricks & Kubernetes with a focus on model deployment and management in microservice architectures, enhancing operational efficiency and scalability in production environments.
- Proficiency in Docker containerization and Kubernetes orchestration for deploying ML models in production environments.
- Strong understanding of A/B testing methodologies.
- Skilled in deploying GPU-based ML/DL models for parallel inference, optimizing computational efficiency and performance for near real-time processing in production settings (preferably using CUDA).
- Experience with open-source LLMs and Whisper is highly desirable and considered a significant plus.
- Knowledge of networking concepts and experience in configuring and optimizing network resources within Azure.
- Proven track record in MLOps, with a focus on MLFlow and Azure technologies.
We Offer
- Technical growth and education.
- International projects in Scandinavian business culture.
- Long-term cooperation across multiple projects and sectors.
- Transparently built relations based on trust and fair play.
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