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ZeroFlucs Linkedin · Posted 7d ago

Senior Data & AI Engineer

Australia

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Company Description

Part of Caesars Entertainment, ZeroFlucs creates the software that makes the sports betting industry tick Same-Game pricing, content generation, odds aggregation and trading automation.


Role Description

We're growing our Data Platform team and hiring a Senior Data & AI Engineer, based in Brisbane, QLD (office in Teneriffe). You'll help own the data and AI platform behind our trading and sportsbook products like real-time betting and pricing data, the lakehouse and analytics layers on top of it, and the ML/AI we build from it working with data scientists, traders and customers across multiple time-zones.

We've kept the title broad on purpose: we care more about the right person than a rigid checklist, and we'll shape the role around your strengths.


What you'll do

A blend of depending on your strengths:


  • Build and operate real-time and batch pipelines (Flink, Kafka, Spark, Iceberg).
  • Develop models and applied AI and classical ML (recommendation, propensity, classification) and LLM features (RAG, agents/tools, prompt engineering) on bet and customer data.
  • Do analysis and measurement - advanced SQL/Python, A/B and hypothesis testing, semantic-layer modelling and dashboards that drive decisions.
  • Ship backend services and integrations (Go / Python / Java) and own your work end-to-end: design -> build -> deploy (tf/k8s) -> support.


About you

  • Strong engineering fundamentals; excellent Python and SQL.
  • Deep skill in at least one of data engineering, applied ML/AI, or analytics with real competence in other categories.
  • Owns problems end-to-end and communicates well across technical and non-technical teams.
  • CS / Data / Stats degree or equivalent experience.


Highly preferred

  • Data: Flink, Kafka, Spark, Iceberg; StarRocks, ClickHouse, Snowflake, Postgres; BI semantic modelling
  • ML/AI: classical ML + feature engineering; applied LLMs (RAG, agents, prompt engineering); bonus: Bedrock, LiteLLM, MCP, vector search
  • Backend/platform: Go / Python / Java, gRPC/GraphQL; Kubernetes, Terraform; cloud (AWS/GCP/Azure)
  • Domain: wagering, gaming or trading experience


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