- Take ML or LLM proof-of-concept projects to production-ready enterprise standards.
- Design and harden data and training pipelines for enterprise ML systems.
- Perform ML platform and MLOps tasks including deployment, versioning, monitoring, and CI/CD for models.
- Build LLM and RAG systems focusing on retrieval quality, evaluation, and cost control.
- Fill deep technical gaps in client engineering teams.
- Conduct technical audits and advisory work on existing ML stacks.
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