ML Engineer

The Company

Machine Medicine Technologies (MMT) uses computer vision and computational statistics to enhance the neurological assessment of patients. Our first product, KELVIN, allows motor assessments in Parkinson s disease to be performed, recorded and used both faster and better than has ever previously been possible. KELVIN-PD is already in use at clinical sites across several countries and possesses a CE mark, being a class-I medical device. MMT aims to build the platform into a generalised tool for patient selection, surgical planning and device programming for machine brain interfacing, a revolutionary therapeutic innovation.

Culture

A fast-moving startup, with an energetic and dynamic team, looking to disrupt the MedTech industry with AI. Our employees are encouraged to take on the sort of career development opportunities that cannot be found at larger, more established, companies. We are in the highly regulated medical device industry, so our engineering team has to have an even greater focus on quality, usability and versatility. We also like to blow off steam, whether that s playing a few rounds of table tennis in the office, or arranging an online gaming session.

Company Benefits

• Competitive salary
• Employee equity programme
• Pension
• Monthly socials
• 25 days annual leave (+UK bank holidays)
• 1 day remote working
• Visa sponsorship

Additional information

• Experience level:Mid/Senior
• Tech stack: Python, AWS, Docker, Torch, sklearn, pandas

About you

You are an ambitious and capable machine learning engineer, with direct experience deploying and maintaining machine learning pipelines in computer vision. You have a superb command of general programming principles and code deployment practices. You care about impact and want to do work that matters.

List of main duties and responsibilities:

• Leading the design and development of ML pipelines
• Deploying machine learning models as microservices into production
• Contributing to our research and academic papers

Requirements:

• Commercial python experience (2+ years)
• Demonstrable experience deploying and monitoring Machine learning models
• Strong understanding of ML techniques and statistical concepts
• BSc, MSc in a relevant quantitative subject (computer science, mathematical engineering, etc)
• Experience with core Python data science packages (NumPy, pandas, sklearn)
• Experience with at least one deep learning framework (PyTorch or TensorFlow)

Desirable:

• Experience with configuration management (Docker, Kubernetes)
• Familiarity with cloud infrastructure (AWS EC2, S3, Batch)
• Good communication and time management skills
• Previous experience in the biomedical sector