Machine Learning Engineer

More about the team

Our team is part of Strategic AI Initiatives, exploring new areas in the healthcare market. Right now, we're working on several innovative AI projects.

One key project is our AI Assistant, an early-stage product with great potential. Our goal is to help doctors provide more attentive care during consultations. We aim to reduce computer-related distractions, improve workflows, and create a more empathetic patient experience thanks to using the AI Assistant (using, among others, Speech Recognition and LLM Models).

How would you be impacting our mission?

• Deploying custom/pre-trained machine learning models into production.
• Implementing ML/LLM-based solutions on scale and evaluating them.
• Validating, monitoring and supporting models & environment in a production setup.
• Monitoring changes in data characteristics in production.
• Selecting the best parameters for inference.
• Optimizing inference.

Requirements

What will help you thrive?

• Growth mindset: nobody ticks all those boxes above, but a willingness to learn is strongly valued here.
• Concentrate on delivering value to the end user; we value a broad perspective rather than fixating solely on specific technologies
• Proficiency of at least 4 years in Machine Learning, encompassing the deployment of models.
• Proficiency in developing APIs and GPU-oriented training and inference.
• Robust command of Python and familiarity with Bash.
• Hands-on experience with machine learning frameworks such as PyTorch and big data technologies.
• Familiarity with Docker, Kubernetes, and cloud platforms tailored for Machine Learning deployment.
• Exceptional communication abilities demonstrated in both written and verbal forms.
• Aptitude for problem-solving and adeptness in conveying intricate concepts efficiently.

Bonus points

• Experience with audio data and speech recognition models.