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Heidihealth.Com.Au

Clinical AI Research Lead

LondonUnited Kingdom
Staff · FullTime · Engineering
POSTED 2 NOVVERIFIED 56M AGO
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Open for
1d
since 2 Nov
Hiring · 30d
68
−4 net · open roles

We’re Heidi.

We're building the future of healthcare by giving every clinician the earth's finest AI Care Partner. Our platform has absorbed the administrative chaos of 175 million patient visits and supported 67 million clinical hours. Today, we support 2.8 million patient sessions a week across 190+ countries, in 110 languages and over 200 specialties.

Healthcare systems are failing us; clinicians spend more time on documentation than on patients, and the human connection that makes medicine worth practicing is eroding. Our mission is simple: double the world’s capacity for care and strengthen the human connection at its heart.

We found product-market fit with a freemium medical scribe that clinicians love. Now, we're expanding. Every task a clinician hands to Heidi is a patient who feels more attended to, a health system unclogged, and a clinician who gets to be a clinician again.

We’ve grown annual recurring revenue from $1 million to $50 million in two years.

To go further, we’ve secured US$340 million: a $100 million Series C led by Blackbird, with Phoenix Court, Point72 Private Investments and Headline, alongside a $240 million growth investment led by General Catalyst’s Customer Value Fund.

If you want to join us in doing work worth shipping, jump in.

The role

Heidi is building AI that works at the frontier of clinical practice. As we pursue medical device registration and expand our clinical trial portfolio and product portfolio, we need someone who can hold the full arc from regulatory strategy to research protocol to working prototypes and translate across all of them.

This role is designed for a rare profile: clinically trained, technically capable, and research-rigorous. You will own the innovation pipeline from problem identification through validated prototype, coordinate the company's clinical research programme, and serve as the internal bridge between product, regulation, and evidence. You will operate as a senior individual contributor with a small specialist team and broad cross-functional mandate.

What you’ll do

Research & Evidence Programme

Lead and support clinical trials and pilots adjacent to product development and regulation from protocol through analysis and dissemination

Design evaluations with research/publication-grade rigour: statistical power, confounder control, reproducible methodology

Provide analytical support company-wide - elevating ad hoc analysis to defensible evidence

Regulatory & Compliance Intelligence

Translate evolving UK and international medical device regulation into actionable product and development constraints

Generate and maintain technical documentation, clinical evaluation reports, and post-market surveillance artefacts - directly analytically supporting the regulatory team.

Partner with compliance to ensure regulatory soundness is built in, not bolted on, a strategic moat, not a checklist

Serve as the accessible regulatory resource for product, engineering, models and commercial teams: making regulation legible, usable and deeply embedded into all engineering practices.

This role is strategic support, and ownership of all product and regulatory adjacent research activities with a strong supporting team to drive progress and delivery.

Cross-functional AI & Research Support

Act as a senior research partner to product squads, commercial teams, and leadership, providing evidence, framing decisions, and raising analytical standards

Supporting commercial requests with tender applications etc…

What you'll need

Clinical

Qualified clinician with active understanding of clinical workflow, risk, and patient safety

Experience in medical device or clinical AI evaluation, including familiarity with MHRA, UKCA, and/or EU MDR frameworks

Research

Postgraduate research training in a relevant field (clinical informatics, AI/ML, health data science, or similar)

Demonstrated ability to design, execute, and disseminate clinical or applied research independently

Fluency in quantitative methods: statistical modelling, NLP evaluation, speech analytics, and performance benchmarking

Source · Heidihealth.Com.AuFirst seen 2 NovOriginal ↗