Senior ML / AI Data Engineer @ UK Startup - 71MN Vietnamese Dong
Join a remote-first, high-autonomy team and leverage your expertise to transform user behavior data into actionable product insights. Collaborating closely with the CTO, you'll design and build data pipelines, ML segmentation models, and LLM-powered features that drive key decisions across our live B2C products. Core tasks include integrating signals from Supabase, PostHog, and RevenueCat, developing internal tooling for behavioral analysis, and contributing to our notification intelligence layer. This role offers an equity-aligned compensation model and the opportunity to shape products used by real customers, not just prototypes.
The ideal candidate has 5+ years' experience in ML engineering, data engineering, or applied AI, with a strong background in Python, data tooling (pandas, dbt, SQLAlchemy), and deploying ML models in production environments. Proficiency with LLM APIs (e.g., OpenAI, Anthropic Claude), vector databases (pgvector, Pinecone, Weaviate), and analytics platforms like PostHog or Mixpanel is required. Strong communication skills and the ability to work independently in a fast-paced, async environment are a must.
Help us turn raw user behaviour into product intelligence. Across our portfolio we have rich data - engagement patterns, subscription signals, session depth, conversion funnels - and we're ready to operationalise it. You'll build pipelines, segmentation models, and LLM-powered features that drive decisions across every product. Hands-on from day one, working directly with the CTO .
Tasks
- Design and build data pipelines consolidating signals from Supabase, PostHog, and RevenueCat
- Build and ship ML segmentation models to identify high-value users, churn risks, and
conversion-ready cohorts - Develop and maintain LLM-powered features: agents, RAG pipelines, personalisation systems Instrument and evaluate AI agent performance using LLM-as-judge and related evaluation patterns
- Build internal tooling for behavioural analysis - session replay, cohort formula tooling, user journey mapping
- Translate data insights into actionable product changes in collaboration with the product team
- Contribute to the notification intelligence layer - ML-driven segmentation and send-time optimisation
Requirements
- 5+ years in ML engineering, data engineering, or applied AI - ideally B2C or product-led
- Strong Python skills and fluency with data tooling (pandas, dbt, SQLAlchemy or similar)
- Experience building and deploying ML models in production - not just notebooks
- Hands-on with LLM APIs: Anthropic Claude, OpenAI, Gemini, or open-source models
- Experience with vector databases and embedding pipelines (pgvector, Pinecone, Weaviate)
- Familiarity with PostHog, Mixpanel, or equivalent product analytics platforms
- Solid SQL skills - comfortable querying PostgreSQL / Supabase at scale
- Independent self-starter who communicates findings clearly to non-technical stakeholders
Benefits
- Live products with real users - not internal tools or greenfield prototypes
- Remote-first, async culture with high autonomy
- Fast-moving team that ships constantly - no endless planning cycles
- Equity-aligned model: we build products we co-own with creators
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