Senior Machine Learning Engineer at Proximie – Beirut | Jobyssey

Proximie is on a mission to improve healthcare by transforming the world’s operating rooms into connected ecosystems of people, devices, and data.

Our Intelligence Suite transforms operating room (OR) performance, keeping teams in sync and workflows on track to maximise throughput. Simultaneously our computer vision and AI capabilities capture real-time data and detect surgical events – improving quality of data outputs. The result: ORs are optimised like never before – with predictive analytics and automated notifications ensuring patients and staff are in the right place at the right time.

Once practitioners are in the OR, our Surgical Suite enables real-time remote access and creates a secure video record of every procedure; improving training, education, and collaboration. It is an intuitive asset which helps instil a culture of continuous learning, accelerates the adoption of cutting-edge medical devices, and enhances surgical performance across the entire global workforce – improving outcomes and saving lives.

Proximie was commercialised in 2019 and is available in over 500 facilities globally.

Check out our Founder and CEO Nadine’s Origins Story here:

Position Overview

As Proximie continues to turn every activity and event in the operating room into comprehensive, structured, and context-rich data that drives better insights and decisions making, 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.

You 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. You’ll also lead the development of intelligent systems that can automatically detect and capture key events in the operating room, designing robust solutions that work across diverse and unpredictable data distributions, tackling challenges like identifying rare events buried in hours of surgical video.

This role demands 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.
Knowledge and experience with AWS is highly desirable.
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.

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