Location
London

Hours
Full Time

Salary
Competitive, commensurate with experience

About the Role
Qureight’s mission is to accelerate clinical trials and ensure breakthroughs in lung and heart disease reach patients without delay. Our AI-powered data and imaging curation platform enables the analysis of clinical imaging and other healthcare data, helping our customers bring treatments to market faster. With offices in Cambridge and London, you will join a multidisciplinary team of clinicians, scientists, and engineers united by an open culture, continuous learning mindset, and a shared mission to help biopharma run faster, smarter trials.

We are building the operational backbone required to deliver at pace without compromising scientific rigour or regulatory compliance. With strong commercial traction and the infrastructure, workflows, and quality frameworks needed to support complex global trials, the next stage is to develop new disease AI models, turn these into commercial products, and deliver them to customers.

As Project Manager, you will lead the delivery through to commercial launch of AI-driven products across our clinical data and imaging platform. You will be a systems thinker comfortable with ambiguity and iterative development, working at the intersection of machine learning and data science, clinical, scientific and software engineering teams, and commercial and partner organisations.

Working closely with Product Management, you will translate cutting-edge ML models into validated, deployable, revenue-generating solutions used in clinical trials and drug development.

Key Responsibilities:
1. Drive end-to-end AI project delivery: manage delivery of new ML-based products from research and prototyping to validation, release, and deployment; support continuous maintenance and improvement; coordinate across ML, engineering, clinical, and commercial teams; design and manage project budgets; manage timelines, dependencies, and delivery risks in a research-heavy environment.
2. Bridge technical and clinical domains: translate between ML engineers, data scientists, software and data engineering teams, clinicians, research partners, and external customers including pharma, biotech, and CROs; ensure models align with clinical use cases, regulatory, and data constraints.
3. Support model validation and real-world deployment: oversee data acquisition and licensing, procurement of cloud and tooling infrastructure, data readiness and quality workflows, model validation in clinical settings, and integration into Qureight’s platform and trial workflows.
4. Enable commercialisation of AI products: collaborate with clinical and commercial teams to support customer pilots and deployments, IP protection, translate technical capabilities into customer value propositions, support marketing plans, and help shape product specifications and delivery models for pharma and clinical partners.

Experience
- Proven track record in project management, product delivery, or similar roles
- Experience managing complex software and machine learning product development, bridging engineering and science disciplines
- Strong understanding of ML lifecycle including training, validation, deployment, and monitoring
- Knowledge of data challenges such as quality, bias, and labelling
- Familiarity with regulated environments such as medical devices, healthcare, or clinical trials
- Experience working in high-growth startups or scaleups
- Ability to connect technical delivery with business outcomes
- Skilled at managing conflicting interests and constraints
- Ability to engage deeply with technical teams without being hands-on

About you
Systematic thinker comfortable with ambiguity and iterative development, excellent communicator with a bias towards execution and delivery, able to work collaboratively across multidisciplinary teams and external partners.

Qualifications
Relevant qualifications in project management, computer science, data science, or related fields are desirable but not mandatory. Demonstrated experience and skills are paramount.