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We are looking for a Machine Learning Engineer to join our team and contribute to the GenAI initiative. In this position, you will focus on creating, enhancing, and fine-tuning backend systems that drive LLM-powered applications utilizing OpenAI APIs. Your expertise in MLOps, CI/CD, observability, and cloud-native tools will be critical in ensuring the performance, reliability, and scalability of AI-driven solutions.
Responsibilities
- Build and enhance backend systems for AI and LLM-powered applications
- Integrate LLM applications into cloud platforms and manage their operations
- Scale AI systems to meet performance and reliability goals
- Create CI/CD pipelines to enable automated deployment processes
- Monitor the performance of AI services to ensure system stability
- Set up observability and logging to track the performance of LLM APIs
- Work with DevOps teams to optimize workflows and improve system reliability
- Collaborate with AI and Data Science teams to expand and refine application features
- Utilize cloud platforms, particularly Azure, for hosting and scaling AI applications
- Design APIs and microservices architecture to enable AI functionalities
Requirements
- A minimum of 2 years of experience in Machine Learning Engineering with a focus on backend and software systems
- Extensive experience in integrating OpenAI APIs and AI services
- Proficiency with MLOps tools such as Orion, ArgoCD, and Opsera for automation of deployments
- Experience using monitoring and observability platforms like Grafana, Dynatrace, or ThoughtSpot
- Strong knowledge of cloud infrastructure, with a preference for Azure, as well as expertise in Apache Spark and Databricks
- Advanced Python programming skills for backend development
- Proven experience in developing APIs and designing microservices architectures
- Fluency in English, both written and spoken, with a proficiency level of B2+ or higher
Nice to have
- Understanding of Data Science concepts and methodologies
- Experience working with Large Language Models (LLMs)
- Familiarity with Natural Language Processing (NLP) techniques and tools