(Senior) Machine Learning Inference Engineer

Company Description

Snke OS™ is a universally deployable digital B2B platform, founded in 2020 & headquartered in Munich. Emerging technologies continue to drive a digital transformation in the healthcare economy. Our founders recognized the potential for value creation by decoupling & deploying their best-in-class platform & team so that other companies can scale up & innovate efficiently. Fueled by AI & big data analytics, Snke OS delivers the platform & infrastructure that enables partners across the healthcare industry to deploy digital solutions for safer & more efficient interventions.

The 150-person Snke OS team brings a wealth of experience to the new company with backgrounds in large platforms, digital health & software-driven medical technology. Let’s impact the industry together! We are looking for pioneers to lead fast & lead first with Snke OS.

Job Description

For our ambitious and growing Data Intelligence department, we are looking for a Machine Learning Inference Engineer with a strong background in software engineering.

In this position, you will

• Work on software development projects that support our machine-learning activities
• Take responsibility for optimization and acceleration of state-of-the-art deep-learning models
• Develop efficient algorithms and data structures
• Contribute to learning-based solutions for a variety of tasks in medical data analysis
• Share your knowledge and provide technical guidance to your colleagues in the development team
• Ultimately have impact on the daily work of medical professionals around the world

Qualifications

• Education in mathematics, physics, computer science or a similar background
• Strong background in software engineering and C++
• Experience with Python and modern machine-learning frameworks
• Experience with model optimization for inference
• Eagerness to be part of a high-skilled, dynamic team where your talent is both, challenged and supported
• Fluency in English, and ideally knowledge of or willingness to learn German

Additional Information

• Centrally located, modern work spaces
• 30 days of vacation plus 24.12. and 31.12.
• Flexible working hours as well as hybrid work model within Germany
• Secure bicycle storage room
• Regular after-work, team & company events
• Great 212m² roof terrace
• International team of supportive colleagues
• Comprehensive training and continuing education opportunities

Interested? Then we are looking forward to receiving your online application!

Contact person: Daniel Sypli