Your work won’t just demo AI—it will reshape healthcare delivery and patient care across the globe.

Responsibilities

Core Focus Areas

• Collaborate with product, engineering, and commercial teams to design, implement, and deploy AI models in hospitals worldwide—ensuring seamless integrated solutions.
• Specify, develop, and fine-tune multi-modal machine learning models (from snake detection in microscopy to surgical tool tracking in live ORs) using state-of-the-art techniques.
• Address real-world challenges, such as kimnoting rare surgical events within hours of video, and building models that adapt to various dominant instruments and team habits in different regions.
• Own the end-to-end ML pipeline—curating data, prototyping models, validating robustness, deploying and maintaining systems for real-world clinical environments.
• Work within Proximie’s infrastructure to enable dynamic AI training, real-time model performance evaluation, and integration with large-scale data lakes.
• Contribute to documentation, mentorship, and team knowledge-building to solidify best practices as the platform evolves.

Requirements & Qualifications

Essential Criteria

• Degree: PhD in ML, computer science, data science, engineering, or related field. Masters qualifications will be considered, but PhD is preferred.
• Experience: Minimum 4 years’ experience in industry applying AI to real-world problems, including hands-on model deployment and impact assessment.
• Deep expertise in ML & CV:
  • Vision-focused ML: demonstrated success in developing computer vision and multi-modal models (e.g. Action Detection, Segmentation, Detections with Context).
  • Conducting large-scale learning across heterogeneous datasets, including distribution shifts (common in global ORs).
• Technical proficiency:
  • Expertise in TensorFlow, PyTorch, or similar frameworks.
  • Fluency in Python, with a software engineering mindset.
• Systemic Engagement: Demonstrated ability to communicate technical complexity to non-technical stakeholders (e.g. hospital leadership).

Highly Valued (Nice-to-have)

• Understanding of MLOps—including pipelines, versioning, deployment, and monitoring.
• Knowledge of AWS (EC2, ECR, Lambda, or SageMaker environments).
• Initial experience with maintaining deployed AI. Learned in post-deployment troubleshooting or patient journey performance analytics.

Why Join Proximie?

Growth & Autonomy

• We encourage ownership, initiative, and bold ideas—employees are empowered to drive innovation.
• Flat, collaborative teams where every voice matters, fostering an environment of trust and innovation.

Workplace Culture

• 22+ days of annual leave.
• Two Wellbeing Days per year.
• Taken or passed “Summer Fridays”—early office exit on the last day of each UK holiday month.
• Backed by an equitable, competitive annual bonus (built on individual contribution).
• A development stipend of £1,000 annually to invest in your growth—whether books, courses, or training.

Flexible & Agile Work

• trust-based work environment: We prioritise results over presence.
• Global workplace: Office locations in the UK, Europe, US and MENA, with opportunities to connect and collaborate worldwide.

Fit & Belonging

As a Diversity-focused organisation, Proximie is committed to equality—everyone is valued and respected for their unique contribution. We do not discriminate on protected characteristics such as race, gender identity, disability, veteran status or any other status protected in law.