Production assignment 08

Hybrid catalog ranker

Specify BM25 plus learned retrieval, ranking, re-ranking, temporal evaluation, and a versioned online path.

The production problem

Marketplace ranking learns from biased clicks and reinforces its own mistakes.

You own the technical recommendation and the evidence behind it. A reviewer must be able to reproduce the decision, identify which assumptions are estimates, and operate the failure path without asking the author.

Sample input

Versioned events or rows with entity ID, event time, availability time, payload, and mature outcome where applicable.

Expected output

A registered artifact plus evaluation report, decision policy, architecture trace, observability plan, and rollback procedure.

Targets

Beat the declared baseline without violating latency, cost, capacity, subgroup, or freshness guardrails.

Deliverables

Submit evidence another engineer can inspect.

  1. 01

    Exposure-aware data contract

    Include assumptions, identity/version fields, one success example, one counterexample, and the command or query used to verify it.

  2. 02

    Candidate recall analysis

    Include assumptions, identity/version fields, one success example, one counterexample, and the command or query used to verify it.

  3. 03

    Ranker and NDCG report

    Include assumptions, identity/version fields, one success example, one counterexample, and the command or query used to verify it.

  4. 04

    Diversity/fallback/latency plan

    Include assumptions, identity/version fields, one success example, one counterexample, and the command or query used to verify it.

Invariants & acceptance

The result must stay true after packaging.

  • All training inputs are knowable at the historical decision cutoff.
  • Raw-input inference after serialization matches the validated reference within declared tolerance.
  • Every artifact and decision can be joined to code, data, features, configuration, and model version.
  • A failed retry is idempotent and cannot publish partial output as complete.
  • Quality is reported by temporal, operational, and affected-user slices—not aggregate only.
  • The rollback or fallback has a tested trigger, owner, and bounded recovery time.
Self-verification protocol

Try to falsify your own recommendation.

  1. Replay one hand-calculated input and one production-shaped batch.
  2. Inject a missing, late, malformed, and out-of-distribution input.
  3. Restart at the worst possible commit boundary.
  4. Load-test the constrained path, including cold start and a failed dependency.
  5. Compare one protected or high-risk slice and document uncertainty.
  6. Have the fallback produce an auditable result before calling the system ready.
Reference production resolution

Candidate generation, ranking metrics, debiasing, and online experiment design.

The full reference stays behind the recorded-attempt control above. Compare architectural choices and invariants, not incidental file names.