Machine Learning Engineer, Proximie
+ Annual Bonus Program
Virtual collaboration for clinicians
Open for applications
Virtual collaboration for clinicians
21-100 employees
Open for applications
+ Annual Bonus Program
21-100 employees
Company mission
Proximie's mission is to save lives by sharing the world's best clinical practices.
Role
Who you are
- 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
- 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
What the job involves
- 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
- 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
Salary benchmarks
Our take
When someone has to go to a hospital, they expect to hand themselves fully over to the doctors and nurses and be in good, safe hands. Unfortunately, due to a variety of factors, not every hospital can offer the best. That is why Proximie, a global health-tech startup was founded in 2016, to take the lead in democratizing surgical skill and reduce variations in quality and care.
Due to Proximie’s platform, collaborative intraoperative guidance is transforming healthcare worldwide. Augmented reality is far more beneficial to delicately and precisely cover voice and video chat. Proximie can be used without headsets and other equipment getting in the way or being cumbersome, and all that is needed is a phone or tablet.
Proximie is rapidly growing in the global healthcare AI market, which will is estimated to grow to $188 billion by 2030. COVID-19 reduced international travel for surgeons, and the company had a 430% increase in usage, with 6,000 live surgeries in 2020. Contracts with medical device companies now provide access to 90% of the operating rooms and cath labs in the EU and US. Proximie collaborates with major medical device companies including J&J, Medtronic, Abbott, Stryker, Smith & Nephew, and Corin as well as in US & UK health systems such as Advent Health, HCA, and the NHS.
Steph
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 3 rounds)
Jun 2022
$80m
SERIES C
Apr 2021
$38m
SERIES B
Total funding: $129m
Company benefits
- Bi-annual bonus programme – based on individual contribution and company performance
- Full private medical cover (optional)
- Central London location near Oxford Circus
- Career advancement opportunities
- Well being days annually and volunteer days
- Summer Fridays
- 25 days of paid leave
Company HQ
Marylebone, London, UK
Leadership
Plastic Surgeon at NHS and Faculty member of Singularity University.
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