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Proximie is on a mission to improve healthcare by transforming the worlds operating rooms into connected ecosystems of people, devices, and data.
Proximies 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.
Unified Data: Creating a single source of truth in the OR.
Video Library: 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 Proximies 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. Youll harness the power of Proximies deep data lakes and apply cutting-edge generative techniques to solve real-world challenges for Proximies 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. Youll 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. 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.
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 Proximies data lakes.
Document solutions and contribute to internal knowledge sharing and capability building.
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 Python and strong software development background.
Experience with MLOps practices, including versioning, deployment, and monitoring of models highly desirable.
Generous annual leave.
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.
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. Employment type Full-time

Job function Engineering and Information Technology
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Location:
London
Job Type:
FullTime

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