AI role · Open offer
Senior ML Engineer — health & insurance AI
Discovery
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At a glance
How you'll work, where, and key listing dates.
- Employment
- Full-time
- Workplace
- Hybrid
- Location
- 1 Discovery Place, Sandton, Johannesburg 2196, South Africa · Hybrid
- Compensation
- ZAR 900k–1.4M/year + bonus
- Experience level
- Senior
- Team
- Vitality & health AI
- Benefits & perks
About this role
What the team is looking for and how this position fits.
Discovery is hiring a Senior Senior ML Engineer — health & insurance AI on the Vitality & health AI team (Hybrid · Johannesburg, South Africa). This is a hands-on role in risk & decision ML—not a generic “AI enthusiast” post.
You will own real-time scoring, monitoring, and governance end to end: problem framing, offline evaluation, safe rollout, and iteration from production signals. Success is measured with clear metrics (quality, latency, cost, or business KPIs)—not slide decks alone.
**Discovery** is South Africa's leading **insurance and wellness** group — **Vitality** rewards and health products — innovating with data from **Sandton, Johannesburg**.
Senior ML Engineer (hybrid Johannesburg): **health risk models**, **wellness personalization**, and **claims intelligence** with regulatory oversight.
About Discovery
- Johannesburg HQ at Discovery Place; Vitality program spans global partners.
- Actuarial and clinical stakeholders shape model governance.
- Strong data science culture across insurance lines.
What you will do
- Build predictive models for wellness engagement and outcomes.
- Implement monitoring for fairness and regulatory reporting.
- Prototype GenAI tools for broker and member support.
Stack & environment
- Python, PyTorch, Spark, Azure.
- Hybrid Sandton.
What we look for
- Insurance, health, or fintech ML; POPIA awareness.
- Eligible to work in South Africa.
Skills we're hiring for
What each capability means for this role—not a keyword checklist.
- Python
Production Python for data pipelines, model code, APIs, and automated tests—not notebook-only workflows.
- PyTorch
Training and inference with PyTorch: reproducible experiments, checkpointing, and deployment-minded exports.
- SQL
Tools & stack
Platforms and products mentioned for this role (APIs, IDEs, vector DBs, CRMs, design tools, etc.).
- DockerTool
Containerized services and reproducible dev environments for ML and LLM workloads.
- AzureTool
Regular use of Azure in the risk & decision ML stack—configuration, debugging, and team conventions.
You're a strong fit if…
Tailored to this listing—use it as a self-check before you apply.
- ✓You can show evidence in your application: Health risk scoring or wellness personalization with compliance notes.
- ✓Several of these show up in recent shipped work—not only on your CV: Python, PyTorch, SQL, Spark, and Docker.
- ✓You have owned real-time scoring, monitoring, and governance in production: debugging live issues, running postmortems, and iterating from real user or business signals.
- ✓You are comfortable with the hybrid rhythm (Hybrid · Johannesburg, South Africa)—onsite collaboration when it matters, deep work when remote.
- ✓You explain trade-offs (quality, cost, latency, safety) in plain language—with numbers or examples, not buzzwords.
Apply
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What the employer asked for
Health risk scoring or wellness personalization with compliance notes.
Sign in with a candidate account to apply
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