Lead Machine Learning Engineer-MLOps at J.P. Morgan
About the role
hackajob is collaborating with J.P. Morgan to connect them with exceptional professionals for this role. JOB DESCRIPTION We are looking for a Senior MLOps engineer to work closely with Data Scientists to build and deploy ML models on a modern MLOps stack. As Lead Machine Learning Engineer on the Recommendation Engine team, you’ll build and maintain pipelines for distributed model training on large compute clusters, batch/real-time model serving, hyperparameter tuning at scale, model monitoring,…
Interview process at J.P. Morgan
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 J.P. Morgan interviewers score on. Upload your resume and this job description; MiPrep generates a rehearsed answer set in your voice from your own projects.