Data / ML Engineer

️ Interest in food retail, fresh food, or supply chain domains What the job involves

Data pipelines - Build, maintain, and improve our ETL/ELT pipelines. Ingest messy client data (CSV exports, varying formats, schema mismatches) and transform it reliably for forecasting.

Production systems - Deploy statistical/ML models and keep them running at scale. Monitor pipelines and models, set up alerting for failures and data quality issues.

Visibility - Build dashboards so the team and clients can see model health and forecast outputs in real time. Surface insights when performance drifts.

Infrastructure ️ - Own our GCP environments, BigQuery setup, dependency management, and release processes.

Code quality - Write well-structured, tested Python with proper version control practices (branching, PRs, code review).

Client onboarding - Own the end-to-end process from receiving a client's first data extract to delivering clean forecast outputs.

Collaboration - Work closely with our Head of Data Science to run, maintain, and troubleshoot existing models. Document systems and runbooks clearly. Team & reporting

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You're a Data/ML Engineer with strong software engineering instincts. You write clean Python, you're comfortable wrangling dataframes, and you know how to build pipelines that don't break at 2am.

Required

1-3 years of commercial experience in data engineering, ML engineering, or a similar role

️ Strong Python skills with hands-on pandas/dataframe experience

Experience building and running data pipelines (ETL/ELT) with orchestration tools

️ Familiarity with cloud platforms (GCP preferred) and tools like BigQuery

️ Comfortable working with messy, real-world data-CSV ingestion, schema validation, inconsistent formats

Able to deploy and monitor models and pipelines in production

Can build and maintain dashboards to give the team and clients real-time visibility into model health and forecast outputs

You love AI tools and use them to build shit fast-Cursor, Claude, Copilot, whatever gets the job done

Clear communicator who documents well and cares about reliability, not just shipping fast

Excited to work in a small, fast-paced startup where you'll take ownership and jump in wherever needed

Desirable

Enough statistics/ML knowledge to retrain, tune, and troubleshoot models-not just wrap APIs

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