Senior MLOps Engineer

Proximie; Greater London; On-site; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Generous annual leave

Well-being days

Birthday day off

Summer Fridays

Annual bonus

Professional development stipend

Flexible hours

Flat structure

Global exposure

Job summary

Proximie is seeking an experienced ML Platform Engineer to own the productionization and scaling of the machine learning stack. You will manage platform infrastructure, model training and inference on AWS SageMaker, and ensure reproducible, observable pipelines across hundreds of live hospitals.

You will collaborate with ML scientists and engineers to ship reliable services, monitor drift and performance, and drive best practices in CI/CD, containerization, and IaC.

Qualifications

• Expert Python and deep hands-on PyTorch experience, TensorFlow welcome.
• Production AWS experience, SageMaker training/processing pipelines.
• Practical MLOps: experiment tracking, model versioning, reproducible training.

Responsibilities

• Turn models into production services meeting latency, cost, reliability targets.
• Maintain SageMaker training, processing, inference workloads and pipelines.
• Make training runs reproducible via configuration-driven approach.
• Build monitoring for model performance, data drift and system health.
• Ship infrastructure via code review using Terraform and PR workflow.
• Document your builds and raise engineering standards.

Skills

Python

PyTorch

TensorFlow

Hugging Face

timm

scikit-learn

NumPy

pandas

OpenCV

AWS SageMaker

MLflow

Terraform

Docker

CI/CD

Git

Testing

CUDA

Tools

Docker

Terraform

Git

CUDA

Job description

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 CEONadine’s Origins Story here:https://www.proximie.com/about-us/

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 decision making, you will be the engineer who makes that intelligence dependable at scale. Using your deep technical expertise and real‑world production experience, you will own the platform and the infrastructure that carry our machine learning solutions out of development and into hundreds of live hospitals, and keep them performing once they are there.

Job Responsibilities

• Take models built by the machine learning engineers / scientists and turn them into production services that meet our latency, cost and reliability targets.
• Build and maintain SageMaker training, processing and inference workloads, and the pipelines that orchestrate them.
• Make training runs reproducible and configuration‑driven, so any result can be rebuilt from code.
• Build monitoring for model performance, data drift and system health, and make sure the right people are alerted when something moves.
• Ship infrastructure through code review rather than the console, using Terraform and a proper pull‑request workflow.
• Document what you build and raise the engineering standard around you.

Requirements

Essential

• Expert Python, with deep hands‑on PyTorch experience (TensorFlow also welcome) and the surrounding ecosystem: Hugging Face Transformers, timm, scikit‑learn, NumPy, pandas, OpenCV.
• Production experience on AWS, specifically Amazon SageMaker: training and processing jobs, pipelines, model registry, endpoints.
• Practical MLOps: experiment tracking and model versioning with MLflow, hyperparameter optimisation, and reproducible, configuration‑driven training runs.
• Containerisation and infrastructure as code: Docker and CUDA‑based GPU images, plus enough Terraform to ship your own model to an environment through code review rather than a console.
• Strong software engineering fundamentals: Git and pull‑request workflow, automated testing, CI/CD.
• Able to explain technical trade‑offs clearly to people who are not engineers.

Desirable

• Event‑driven and streaming architectures on AWS: Step Functions, Lambda, Kinesis, ECS, DynamoDB.
• Model monitoring in production: inference logging and drift detection.
• Exposure to healthcare, medical devices or another regulated industry.

Why Work for Proximie?

• You will be encouraged to grow in your role, take ownership and gain responsibilities.
• 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.