codax · 1 day ago
Senior Applied ML Engineer, Marketing Systems
San Francisco Bay Area
Full-time
Hybrid
Senior Level
5+ years expCodax is a company focused on enhancing marketing outcomes through automated decision-making and robust data integrations. They are seeking a Senior Applied ML Engineer to build and maintain applied ML systems and backend infrastructure that support marketing decisioning and measurement.
Marketing & Advertising
Responsibilities
Build systems that recommend and optimize marketing actions (e.g., budget allocation, pacing, creative/ad selection, audience targeting signals, channel mix)
Develop learning loops from outcomes: experiment design, counterfactual/holdout analysis (when applicable), offline evaluation, and online monitoring
Implement ranking/bandits or constrained optimization approaches where they fit (ROI under guardrails, budget constraints, frequency caps, etc.)
Work with noisy, delayed feedback signals (attribution limitations, conversion lag, partial observability)
Design data models for campaigns, spend, conversions, events, and identity signals; unify across platforms
Build pipelines for ingestion, normalization, deduping, and reconciliation (spend/conversion mismatches, late-arriving data, API quirks)
Improve measurement robustness (server-side events, event schemas, model features, privacy-aware aggregation)
Build backend services/APIs that expose decisioning outputs and integrate with execution workflows
Implement orchestration primitives: queues, schedulers, state machines for 'plan → launch → monitor → adjust.'
Engineer for production realities: rate limits, retries, idempotency, backfills, observability, and SLAs
Create internal tooling for debugging decisions (why the system did X), data QA, and replay
Qualification
Required
5–10+ years of experience shipping production systems, with meaningful time in applied ML
Strong coding ability and software fundamentals (you can build real services, not just notebooks)
Experience with at least some of: Applied ML for optimization, ranking, forecasting, or decisioning under constraints
Marketing/adtech data (campaign hierarchy, spend, ROAS, CPA, conversion lag, attribution caveats)
Production ML: feature pipelines, model training/evaluation, deployment, monitoring, model/data drift
Building backend systems that handle messy external APIs and high data volume
Comfortable working in ambiguity and iterating quickly with product/customer feedback
Preferred
Hands-on experience integrating or working with major ad APIs (Meta/Google/TikTok/etc.)
Experience with experimentation platforms, bandits, uplift modeling, or causal inference in real systems
Familiarity with privacy/measurement shifts (CAPI, iOS changes, consent modes)
Experience designing guardrails for automated systems (budget caps, safety checks, “do no harm” constraints)
Benefits
Founding Level Equity
Company
codax
Codax is an enterprise Signal Based Marketing firm based in London, helping brands run ABM from real buying signals.
11-50 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase