Staff Machine Learning Engineer - AI Solutions

About the Role

Join Orbem as a Staff Machine Learning Engineer and be part of a transformative journey in AI technology. As a Staff Machine Learning Engineer remote, you will help us industrialize MRI technology, delivering non-invasive insights into various biological datasets. Your expertise will be pivotal in shaping the future of AI-powered MRI imaging.

What You'll Do

• Lead the design and implementation of scalable ML systems.
• Build and improve code for training ML models, focusing on modularity and robustness.
• Collaborate with data scientists to train and fine-tune ML models.
• Optimize and troubleshoot production ML code, ensuring low latency and efficient memory usage.
• Deploy and monitor ML models in production, ensuring stability and performance.
• Guide the team in adopting best ML engineering practices for consistent, production-ready AI developments.

Requirements

• Deep knowledge of PyTorch and distributed training.
• Experience in ML system design and optimizing model architectures.
• Strong Python coding skills with a focus on best practices and design patterns.
• Experience with CI/CD pipelines and cloud providers for scaling ML workflows.
• Proven technical leadership in cross-functional initiatives.

Nice to Have

• Experience with CUDA and GPUs for accelerated computing.
• Familiarity with 3D data and computational challenges.
• Background in ML applications in healthcare, including data privacy techniques.

What We Offer

• International environment with 40+ nationalities.
• Attractive compensation package with stock options.
• Visa and relocation support for your move to Germany.
• Learning and development budget of €1,750 annually.
• Flexible hours and home office options.
• 30 days paid leave and personal leave flexibility.
• Work from anywhere for up to 60 days per year.

As a Staff Machine Learning Engineer remote, you will have the opportunity to lead impactful projects and shape the future of AI technology at Orbem. We are committed to helping you discover your strengths while also learning from you.