Staff Machine Learning Engineer (f/m/d)

We see the potential inside everything and everyone. Starting with you.

Orbem uses AI to industrialize MRI, delivering non-invasive insight into everything from fruits to eggs to the human body. We are transforming what is becoming the world’s largest biological dataset into actionable intelligence to reduce waste, increase quality, and accelerate the shift toward a more sustainable and healthier future.

Headquartered and founded in Munich, Germany, with an office now in Houston, Texas, our world-class team is scaling inside-out technology to transform how humanity sees and understands biological matter.

Help us see what’s possible. Join us.

Staff Machine Learning Engineer (f/m/d)

• Starting date: As soon as possible

• Yearly Salary: €90,000 - €100,000 (fixed range, annual gross)

• Stock Options: €40,000 to €80,000

• Benefits: Up to €5,000 annually

• Work model: Full-time, Hybrid (Munich, Germany)

Your role

As a Staff Machine Learning Engineer, you will be at the forefront of building the intelligent systems that power Orbem’s next-generation technology. You’ll design and deliver scalable, production ready ML solutions that move seamlessly from prototype to real-world deployment. Partnering closely with data scientists and software engineers across teams, you’ll shape the core architecture that brings breakthrough ideas to life.

You’ll be a driving force for excellence, defining best practices, elevating engineering standards, and championing high-quality machine learning at every stage. With your production mindset, passion for impact, and vision for what’s possible, you’ll help unlock the next era of AI-powered MRI imaging propelling Orbem toward its ambition of becoming a true Machine Learning powerhouse.

Your day to day

On a typical day you would: 

• lead design and implementation of ML systems.

• build and improve code for training ML models, prioritizing modularity, scalability and robustness.

• collaborate with data scientists in training and fine-tuning ML models.

• optimize and troubleshoot production ML code and models, focusing on latency and memory footprint.

• deploy and monitor ML models in production, ensuring model stability.

• grow the know-how in production ML tools and concepts within the team.

• guide the team in adopting the best ML engineering practices, ensuring a consistent and production-ready approach across all AI developments.

Your experiences and skills

Fit to our values

• We own every challenge: we enjoy complexity and thrive under uncertainty.

• We strive for better: we seize any opportunity for growth and challenge the status quo. We are constantly learning and improving.

• We imagine new frontiers: we think beyond “doable” and “reasonable”. We design a sustainable and healthy future together.
  

Machine Learning

• You have deep knowledge of pytorch and distributed training.

• You are experienced in ML system design.

• You bring experience in optimizing model architectures for both efficient inference and training.

• You have a history of building and automating complex data pipelines for ML.

• You are familiar with tools for ML in production and model deployment.
  

Software Engineering and Automation

• You have strong python coding skills, you are an advocate and expert in best practices and design patterns.

• You have experience with version control tools and tools for creating reproducible, containerized environments.

• You are well versed in CI/CD pipelines.

• You have experience working with Cloud providers to scale and automate ML workflows.

Leadership and business acumen

• Proven technical leadership on cross-functional initiatives, successfully guiding complex projects that span multiple engineering teams.

• Strategic influence in shaping the long-term technical roadmap for a product or platform, ensuring engineering decisions align with business goals.

• High technical judgment and a pragmatic approach to decision-making, with a demonstrated ability to balance deep technical work with product deadlines.

What makes you stand out from other candidates

• You have experience with CUDA and GPUs to facilitate accelerated computing.

• You have worked with 3D data and are familiar with related computational challenges.

• You worked with ML in healthcare, and are familiar with data privacy and security challenges and techniques like federated learning.

What we offer

International Environment: Join a team with 40+ nationalities across 5 continents, all driven by a shared purpose: shedding light on the world’s toughest challenges.

Attractive Compensation Package:

• Stock Options: Share in Orbem’s success.

• Visa & Relocation Support: Seamless support for your move to Germany.

• Learning & Development: €1,750 annual budget for personal growth.

• Fitness Membership: Access to Urban Sports Club or Wellpass.

• Childcare Reimbursement: Support for Kita/Kindergarten fees.

• Deutschland Ticket: Full coverage of public transportation.

Work-Life Integration:

• Flexible Hours & Home Office: Work when and where it suits you.

• WFH Perks: Get €185 to upgrade your home office + a sleek external monitor on us!

• 30 Days Paid Leave: Plenty of time to recharge.

• Personal Leave: Flexibility for life’s important moments.

• Work from Anywhere: Experience new cultures and environments for up to 60 days per year.

Make a Difference: Join an ambitious, fast-growing team working on breakthrough technology. In our scale-up environment, you’ll be free to lead your projects and make an impact. We provide a platform for you to explore, innovate, and define your vision for the future. At Orbem, we’re committed to helping you discover your strengths, and while we aim to teach you, we also want to learn from you. 

Your team

As a Staff Machine Learning Engineer, you become part of our diverse and international team. Learn more about the team members, their work and challenges here: www.orbem.ai 

At Orbem, we're committed to building a smart, diverse team, and we recognize that self-doubt can prevent talented individuals from applying. If you feel you don't meet every requirement, we'd love to hear from you anyway!