Data Ops and ML Engineer
Há 4 dias
Data Ops and ML Engineer – AI-Native B2B SaaS (Remote with UK Team) We’re hiring a Data Ops & ML Engineer to help scale an AI-native B2B SaaS platform that turns real customer conversations and commercial data into actionable insight for revenue teams. This is a hands-on, high-ownership role at a critical stage: the product MVP is complete, early users are onboarding, and the focus now is on data reliability, ML quality, and platform scale ahead of a wider launch in 2026. If you enjoy working across data pipelines, LLMs, and product teams and want your work used directly by customers - this role offers real impact. The Opportunity You’ll sit at the intersection of Data Engineering, ML, and Product , owning the foundations that make AI-driven insight trustworthy, explainable, and scalable. This is not a research-only ML role. You’ll be responsible for: ingestion reliability data quality and lineage prompt and model performance observability and governance You’ll work closely with Fullstack Engineers, Product, DevOps, and the founding team to rapidly iterate and improve real customer outcomes. What You’ll Be Doing Data Operations & Ingestion Build and extend automated ingestion pipelines (email, transcripts, files, conversational tools) Define and maintain metadata, tagging, and traceability from source → insight Own data validation, schema alignment, and error monitoring Partner with DevOps on observability and diagnostics ML / LLM Engineering Improve prompt design, structured outputs, and error handling Reduce hallucination risk and improve grounding and relevance Optimise latency, cost, and performance of LLM workflows Introduce evaluation metrics for insight quality and usage Support scalable deployment of models and future RAG workflows Product & Collaboration Work closely with Product to translate commercial needs into data and ML decisions Collaborate with Engineering on architecture and scaling decisions Help shape future insight categories, workflows, and onboarding frameworks What We’re Looking For Technical Experience 4+ years in data engineering, ML engineering, or hybrid Data/ML roles Strong Python experience Experience with cloud-native data and ML workloads (GCP preferred) Hands-on experience with LLM APIs and prompt-driven systems PostgreSQL and data modelling experience Familiarity with ingestion / orchestration tools (e.g. Airbyte, Composer, similar) Experience implementing monitoring, logging, and alerting for data or ML systems Domain & Ways of Working Experience in B2B SaaS environments Comfort operating in early-stage or high-ambiguity settings Strong understanding of data governance, security, and privacy Able to balance speed with reliability and explainability Soft Skills Ownership mindset — accountable for outcomes, not just tasks Clear communicator who can translate technical decisions into business impact Collaborative partner to Product, Engineering, and Leadership Pragmatic, delivery-focused, and user-centred Location & Working Model Remote (Portugal, Eastern Europe) Core overlap required: 10:00–16:00 UK time Start: Ideally February 2026 Compensation aligned with local market median for Data / ML Engineers Final package dependent on experience and location Why This Role? Build AI systems that are used directly by customers Own data and ML foundations from an early growth phase Work in a modern, cloud-native AI environment High autonomy and influence over technical direction Clear pathway to senior or lead Data / ML responsibility as the team scales
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