Senior Machine Learning Engineer

• 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
• 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

Benefits

• Bi-annual bonus programme – based on individual contribution and company performance
• 25 days of paid leave
• Full private medical cover (optional)
• Central London location near Oxford Circus
• Career advancement opportunities
• Well being days annually and volunteer days
• Summer Fridays- 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
• Knowledge and experience with AWS is highly desirable
• Proficiency with Python and strong software development background
• 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
• 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
• 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
• Ability to communicate complex technical concepts clearly to non-technical stakeholders
• Experience with MLOps practices, including versioning, deployment, and monitoring of models highly desirable
• Proficiency with deep learning frameworks such as TensorFlow/PyTorch