Overview
The Machine Learning Engineer will play a vital role in a long-term project focused on deploying advanced machine learning solutions within a retail environment. This position involves collaborating with various teams to integrate Generative AI models into production systems, ensuring scalability and maintainability. The engineer will work in a hybrid setting, contributing their expertise to enhance workflows and systems integration.
Responsibilities
- Develop and deploy end-to-end machine learning models into production environments.
- Build RESTful and GraphQL APIs for integration of machine learning systems with front-end and back-end platforms.
- Implement monitoring and alerting systems for machine learning pipelines.
- Collaborate with cross-functional teams to deliver scalable software solutions.
- Utilize cloud services (AWS, GCP) and DevOps practices for efficient operations.
- Work with event-driven architecture and streaming technologies such as Kafka.
- Iterate on solutions based on team feedback and user needs.
Requirements
- Proven experience in end-to-end machine learning deployments, particularly with Generative AI.
- Strong programming skills for building RESTful and GraphQL APIs.
- Knowledge of monitoring best practices for AI pipelines, such as Langsmith or Langfuse.
- Familiarity with cloud platforms (AWS or GCP) and DevOps practices (CI/CD, Docker, Kubernetes).
- Experience with event-driven architecture and streaming technologies.
- Understanding of chat agents and customer service systems is a plus.
- Excellent problem-solving skills and effective communication abilities.