ML Engineer

Description

The company builds AI tools that cut the administrative work of healthcare professionals, so clinicians can spend more of their time on patient care.

The team is looking for a Machine Learning Engineer to help develop, improve and scale the AI systems behind these products.

You will work where applied machine learning, software engineering and product development meet, and help move ML work from experiments into production alongside engineers and cross-functional colleagues.

You will have ownership of your work, a direct line to the people who use it, and a say in technical direction for AI products that make clinicians' jobs easier.

The role suits someone who likes hard technical problems, works quickly and wants to see their work have a clear effect.

Responsibilities

• Build, assess and refine machine learning models and the AI features that products depend on.
• Create and maintain production ML pipelines, services and the infrastructure that supports them.
• Design experiments and evaluation methods that show how well models perform, how reliable they are and how they behave.
• Work with product and engineering colleagues to turn user needs into workable technical solutions.
• Make ML systems in production more scalable, efficient and reliable.
• Look into model failures, find where things can improve, and iterate based on feedback from real use.
• Help shape technical decisions and engineering practices across the full ML lifecycle.

Requirements

• Solid software engineering fundamentals and experience building production systems.
• Practical experience developing and deploying machine learning solutions.
• Proficiency in Python and familiarity with current ML frameworks and tools.
• Experience measuring model performance and improving systems through experimentation.
• Understanding of ML infrastructure, deployment, monitoring and keeping production systems reliable.
• Able to work independently, communicate clearly and collaborate across disciplines.
• Comfortable with a quick pace and with technical and product requirements that change over time.
• Experience with large language models, generative AI or speech-related ML systems.
• Experience with model evaluation, fine-tuning or inference optimization.
• Familiarity with healthcare technology or other high-reliability product environments.
• Experience building ML products at an early-stage startup.

Conditions

Team: Engineering.

Employment type: full-time.