• Familiarity with agent frameworks (such as Langchain, Langgraph, IllamaIndex)
• Familiarity with developing RAG systems
• Experience with Natural Language Processing (NLP)
• Familiarity with monitoring tools (such as DataDog or Langfuse)
• Any associate cloud certification (AWS preferred)

Responsibilities:

• Design scalable data pipelines and infrastructure for enterprise ML systems
• Implement ML models and systems into production
• Collaborate with data scientists and software engineers
• Deploy scalable tools and services for machine learning training and inference
• Evaluate new technologies to improve ML system performance and reliability
• Apply software engineering best practices, including CI/CD, to ML development
• Facilitate the development and deployment of ML proof-of-concepts
• Review, refactor, optimize, containerize, deploy, version, and monitor ML models
• Implement monitoring and alerting solutions to ensure the reliability and performance of machine learning systems
• Optimize and automate the machine learning deployment process to ensure efficiency and reproducibility
• Collaborate with cross-functional teams to troubleshoot and resolve issues related to machine learning deployments
• Stay updated with industry trends and apply knowledge to drive innovation
• Promote industry best practices and enhance team expertise

• Competitive compensation with benefits, paid vacation, and sick leave.
• The opportunity to work with a globally diverse team of top engineering talent on the industry’s toughest engineering challenges.
• Ultra-flexible working conditions – we provide a generous office equipment allowance so you can work from home, we can also provide you with a desk at an office/coworking facility near you, or use both. No business travel necessary.
• An enjoyable, start-up work environment, with excellent opportunities for professional growth and development.
• Flexible working hours – as a remote-first company, our focus has always been on getting the job done well, not when or where it gets done.

Originally posted on Himalayas