Back to SearchSenior Machine Learning Engineer
AI Engineering
& 7 others
Choose an option
We are looking for a Senior Machine Learning Engineer to join our team and contribute to the success of the GenAI initiative. In this position, you will focus on building, enhancing, and optimizing backend systems to support LLM-powered applications using OpenAI APIs. Your expertise in MLOps, CI/CD, observability tools, and cloud-native platforms will be key to ensuring the scalability, reliability, and efficiency of AI-driven solutions.
Responsibilities
- Design and enhance backend systems to support AI and LLM-based applications
- Deploy and manage LLM applications within cloud environments
- Optimize AI systems to meet performance and reliability standards
- Develop automated deployment workflows using CI/CD pipelines
- Monitor and maintain the stability of AI services
- Establish observability and logging systems to track LLM API performance
- Work with DevOps teams to enhance workflows and ensure system reliability
- Collaborate with AI and Data Science teams to improve and expand application capabilities
- Utilize cloud platforms, particularly Azure, to deploy and scale AI solutions
- Create and implement APIs and microservices to enable AI-powered functionalities
Requirements
- A minimum of 3 years of experience in Machine Learning Engineering with a focus on backend and software development
- Extensive experience integrating and working with OpenAI APIs and similar AI services
- Proficiency in using MLOps tools such as Orion, ArgoCD, and Opsera for deployment automation
- Hands-on experience with observability and monitoring tools, including Grafana, Dynatrace, and ThoughtSpot
- Strong knowledge of cloud platforms, especially Azure, along with expertise in Apache Spark and Databricks
- Advanced Python skills for backend development and implementation
- Demonstrated experience in designing and building APIs and microservices architectures
- Fluency in English, both written and spoken, at a B2+ level or higher
Nice to have
- Understanding of Data Science principles and methodologies
- Experience working with Large Language Models (LLMs)
- Familiarity with Natural Language Processing (NLP) techniques and tools