Machine Learning Engineer

We are seeking a Machine Learning Engineer to join our team and support the GenAI initiative. In this role, you will focus on designing, improving, and optimizing backend infrastructure to power LLM\-based applications using OpenAI APIs. Your skills in MLOps, CI/CD, observability, and cloud\-native technologies will be essential to ensure the reliability, scalability, and efficiency of AI\-driven systems. **Responsibilities** * Develop and improve backend infrastructure for AI and LLM\-based solutions * Integrate and oversee LLM applications within cloud environments * Scale AI systems to meet performance and reliability requirements * Implement automated deployment processes through CI/CD pipelines * Track and maintain the performance of AI services to ensure consistency * Establish logging and observability frameworks for monitoring LLM API performance * Collaborate with DevOps teams to streamline workflows and enhance system dependability * Work closely with AI and Data Science teams to develop and enhance application features * Leverage cloud platforms, especially Azure, to deploy and scale AI\-powered applications * Design and build APIs and microservices to support AI\-driven functionalities **Requirements** * At least 2 years of experience in Machine Learning Engineering with a focus on backend and software development * Strong expertise in integrating and working with OpenAI APIs and other AI services * Hands\-on experience with MLOps tools such as Orion, ArgoCD, and Opsera for deployment automation * Proficiency with monitoring and observability tools, including Grafana, Dynatrace, and ThoughtSpot * Comprehensive knowledge of cloud platforms, particularly Azure, as well as Apache Spark and Databricks * Advanced Python programming skills for backend development and implementation * Proven experience in designing and building APIs and microservices architecture * Fluency in English, both verbal and written, with a minimum proficiency level of B2\+ **Nice to have** * Knowledge of Data Science principles and workflows * Experience with Large Language Models (LLMs) * Understanding of Natural Language Processing (NLP) methodologies and applications