ML Engineer

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