Machine Learning Engineer at Convergenz
About the role
Build RAG and document-processing pipelines on the Databricks lakehouse - ingestion, OCR of mixed-quality sources, chunking, embedding, and retrieval. Build LLM workflows for summarization, structured extraction, and evidence-grounded generation with source attribution. Generate synthetic document corpora with the fidelity and quality variation needed for meaningful results. Stand up the evaluation harness - retrieval quality, groundedness and hallucination checks, structured-output validity, h…
Interview process at Convergenz
General interview process (this company's specific loop isn't published - reach out if you have insider info).
- Recruiter phone screen - typically 20-40 min
- Technical screen - 1 coding problem or take-home; format varies by company
- Onsite / virtual loop - typically 4-6 rounds over 2-3 weeks; exact split of coding, systems design, and behavioral varies by role and location
Platforms used: unknown — MiPrep tested compatible with major platforms
How to prepare
MiPrep helps you rehearse the specific cadence and question types Convergenz interviewers score on. Upload your resume and this job description; MiPrep generates a rehearsed answer set in your voice from your own projects.