Back to SearchMachine Learning Engineer
AI Engineering
& 7 others
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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