Technical Priorities and Challenges Questions
Identify the team's current technical priorities, pain points, and technical roadmap including architecture, technical debt, platform and tooling constraints, and business intelligence or data infrastructure considerations. Candidates should be able to discuss the current data stack and workflows, trade offs between short term fixes and longer term redesigns, success criteria for technical initiatives in the first 90 days and first year, and how their technical experience and decisions would address the team constraints while aligning with product goals.
HardTechnical
0 practiced
You must develop a one-year technical roadmap that balances eliminating critical technical debt and delivering three major product features. Explain how you'd allocate resources, schedule milestones, and negotiate scope with product managers. Include guardrails to prevent re-accumulation of debt.
MediumTechnical
0 practiced
Design a plan to introduce model interpretability tests into the CI pipeline so that changes in explanations (feature attributions) are treated as regressions. Explain how you'd baseline explanations, compare them across model versions, and avoid false positives due to natural variability.
EasyTechnical
0 practiced
List and briefly explain the core components of a production model-serving architecture for real-time inference (components such as API gateway, model router, model container, feature cache, telemetry, etc.). For each component state one key constraint (latency, cost, throughput, consistency) that often drives design choices.
MediumTechnical
0 practiced
Your engineering lead asks you to quantify the ROI of refactoring the model-serving layer into separate microservices (route, pre-process, model, post-process). Propose a set of business and technical metrics you would use to measure ROI, how to collect them, and an A/B style experiment to validate the refactor's benefit.
MediumTechnical
0 practiced
Data drift has been detected for a key feature. Explain how you would decide between scheduled retraining, on-demand retraining, and switching to an online learning approach. Discuss operational complexity, validation, and rollback strategies for each option.
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