Senior MLOps Engineer Role

New

Skills

AWS Docker Engineer Etl Pipelines Generative AI Kubernetes Machine Learning Python Restful Apis

Join Upwork’s Algorithms and Research team as a Senior/Lead MLOps Engineer and help transform the world’s leading work marketplace. In this fully remote, long-term contract position, you will productize advanced AI technologies—including Generative AI and Large Language Models—to enhance Upwork’s core search, recommendation, and matching functionalities. Collaborate with a globally distributed team and drive impactful, scalable solutions that support millions of users worldwide.

Job Overview
  • Lead the deployment and optimization of machine learning models, focusing on Generative AI, LLMs, and knowledge graphs.
  • Design, build, and maintain robust ML infrastructure and data pipelines in a cloud-native environment.
  • Integrate APIs and support large-scale data ingestion, model serving, and real-time system monitoring.
  • Contribute to Upwork’s multi-year knowledge graph initiative and collaborate with cross-functional teams.
Key Responsibilities
  • Develop, integrate, and maintain knowledge graphs and graph databases.
  • Deploy, monitor, and optimize machine learning models in production.
  • Design and implement retrieval-augmented generation systems for improved search and recommendations.
  • Build and maintain ETL pipelines and ensure seamless data flow from ingestion to model serving.
  • Develop and integrate APIs for serving ML models and knowledge graph data to platform applications.
  • Implement monitoring, alerting, and active learning systems to ensure model reliability.
  • Collaborate with global teams to deliver impactful, scalable ML solutions.
Required Skills & Qualifications
  • 5+ years of experience deploying and maintaining machine learning models in production.
  • Expertise in knowledge graph development, graph databases (e.g., Neo4j, TigerGraph), and data integration.
  • Proficiency in Python (Java/Golang a plus).
  • Experience with scalable, cloud-based architectures (AWS preferred; GCP/Azure valued).
  • Hands-on experience with Docker and Kubernetes.
  • Strong understanding of Generative AI, LLMs, and modern ML frameworks.
  • Proven ability to build and maintain ETL pipelines and integrate with relational databases.
  • Familiarity with RESTful API development and best practices.
  • Excellent problem-solving skills and proactive, collaborative mindset.
  • Experience with large-scale, multi-year knowledge graph projects is a plus.

Job Type: Remote

Salary: Not Disclosed

Experience: Entry

Duration: 12 Months

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