Five billion people in the world do not have access to safe and affordable surgery, and this is a problem everywhere, not just in developing countries. Proximie is on a mission to improve healthcare by transforming the world’s operating rooms into connected ecosystems of people, devices, and data.

Proximie’s advanced telepresence and cloud data solutions ensure seamless information flow in and out of the operating room (OR). Once collected, this data becomes a “single source of truth,” allowing healthcare professionals to utilize powerful analytics to identify patterns, trends, and bottlenecks, as well as uncover optimization opportunities.

Proximie empowers medical device companies and healthcare organizations with operating room intelligence to drive productivity and innovation.

Our key solution areas are:

• Real-time Connectivity: Be in the operating room from anywhere. 
• Unified Data: Creating a single source of truth in the OR. 
• Analytics and Insight: Turning incisive insight into decisive results. 
• Video Library: Learn more from every procedure.

Proximie was Founded in 2016 by Dr. Nadine Hachach Haram, an NHS surgeon and is headquartered in London with offices in the United States and Lebanon. Proximie has 100 employees today and is deployed in over 50 countries.

Check out Nadine’s Origins Story here: https://www.proximie.com/about-us/

Position Overview

As Proximie continues to turn every activity and event in the operating room into comprehensive, structured, and context-rich data that drive better insights and decision making we are seeking two machine learning engineers to join our data team. Using your deep technical expertise and real-world experience you will be instrumental in developing and deploying machine learning solutions that improve clinical outcomes, drive productivity and support Proximie’s continuing evolution into the unrivalled champion of the intelligent operating room.

The first machine learning engineer position will work with multi-modal data (audio, vision, and language) to curate, consolidate, and augment retrospective and prospective datasets that fuel the development of advanced machine learning solutions. You’ll harness the power of Proximie’s deep data lakes and apply cutting-edge generative techniques to solve real-world challenges for Proximie’s customers.

The second machine learning engineer position will lead the development of intelligent systems that can automatically detect and capture key events in the operating room. You’ll design robust solutions that work across diverse and unpredictable data distributions, tackling challenges like identifying rare events buried in hours of surgical video.

Both roles demand creativity, precision, and a deep understanding of real-world machine learning at scale. If you're excited by complex problems with life-changing impact and want to build tech that operates in the most critical environments, we’d love to hear from you.

Responsibilities

• Collaborate with product, engineering and commercial teams to develop and deploy AI models for real world application in hospitals all over the world.
• Design, train and validate machine learning mono and multi-modal models using state of the art approaches.
• Develop models and derived tools robust to the heterogeneity of operating room environments. With customers all over the world operating rooms are often different which creates unique opportunities for problem solving and model design.
• Own the full model lifecycle including but not limited to data curation, model implementation, training, validation, deployment, and maintenance.
• Development within Proximie environment to enable dynamic model training and performance evaluation while integrating with Proximie’s data lakes.
• Document solutions and contribute to internal knowledge sharing and capability building.

Requirements

• PhD in a machine learning field such as computer science, data science, engineering, or a related field. Masters considered but PhD preferred.
• Minimum of 4 years’ hands-on experience in industry, developing and deploying AI solutions which solve real-world problems.
• Expertise in developing, training and fine-tuning machine learning and multi-modal models. Experience in training models with data originating from heterogeneous distributions is highly desirable.
• Deep knowledge of a variety of traditional machine learning, deep learning and generative AI methods for both supervised, self-supervised and unsupervised learning with an emphasis on vision.
• Proficiency with deep learning frameworks such as TensorFlow/PyTorch.
• Proficiency with Python and strong software development background.
• Experience with MLOps practices, including versioning, deployment, and monitoring of models highly desirable.
• Ability to communicate complex technical concepts clearly to non-technical stakeholders.

Why Work for Proximie?

• You will be encouraged to grow in your role, take ownership and gain responsibilities. Proximie’s values are Ownership, Deliver Results, Build Trust and Go Beyond.
• Generous annual leave.
• Two “well-being” days per year plus the day off for your birthday.
• “Summer Fridays” – early office closing on Fridays during summer months.
• Annual bonus programme – based on individual contribution.
• To support your professional growth, all permanent employees will have access to an annual stipend of £1,000 to assist with personal development activities.
• Flexible working hours - we trust our people to manage their time and to focus on wider results.
• A flat organizational structure where every opinion matters, ideas are cultivated, and innovation is encouraged.
• Proximie is a truly global company with teams across the UK, Europe, United States and the Middle East with that you will have opportunities to see the world.

Proximie is an equal-opportunity employer. We are committed to providing a work environment that supports, inspires, and respects all individuals. We do not discriminate on the basis of race, colour, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under the law.