Collaborate with data scientists and engineers to orchestrate LLMs into AI workflows.
Implement vector storage and indexing for NLP.
Develop tools for prompt management, automated evaluations, and observability.
Monitor and improve agentic systems performance for accuracy and efficiency.
Build data pipelines for high-volume structured and unstructured data.
Integrate third-party AI APIs to extend system functionality.

🎯 Requirements

Bachelor's or Master's in CS, Engineering, Data Science, or related STEM.
4+ years in ML engineering or data engineering.
Strong Python or other high-level language used in ML.
Experience deploying LLMs and automated evaluation pipelines.
Architecting multi-agent systems with tool-calling and memory.
Nice-to-have: Cloud (AWS, GCP), Docker, Git; API integration.

🎁 Benefits

High-Impact environment
Professional development opportunities
Flexible and collaborative culture
Global opportunities
Vibrant community
Total rewards

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