Senior Machine Learning Engineer in London

Senior Machine Learning Engineer in London

London Full-Time 60000 - 80000 £ / year (est.) Home office (partial)
Proximie

At a Glance

  • Tasks: Develop and deploy AI solutions to transform operating rooms and improve healthcare outcomes.
  • Company: Proximie is revolutionising healthcare with cutting-edge technology in operating rooms.
  • Benefits: Generous leave, well-being days, flexible hours, and a £1,000 annual development stipend.
  • Other info: Join a global team and enjoy a flat structure where your ideas matter.
  • Why this job: Make a real impact on global healthcare while working with innovative tech and diverse teams.
  • Qualifications: PhD preferred, 4+ years in AI, expertise in machine learning and software development.

The predicted salary is between 60000 - 80000 £ per year.

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

  • Ph D in a machine learning field such as computer science, data science, engineering, or a related field. Masters considered but Ph D 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 Tensor Flow/Py Torch.
  • 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.

#J-18808-Ljbffr

Proximie

Contact Details:

Proximie Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Machine Learning Engineer in London

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Proximie!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Machine Learning Engineer at Proximie.

Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Proximie.

Apply Directly through Our Website

When you find a suitable opening like Senior Machine Learning Engineer at Proximie, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Senior Machine Learning Engineer in London

Machine Learning
AI Model Development
Data Curation
Model Implementation
Training and Validation of Models
Multi-modal Data Processing
Deep Learning Frameworks (TensorFlow/PyTorch)

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Proximie, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Proximie. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Proximie

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Proximie!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.