Data Scientist-Jobs in Deutschland

Who we are:

We are a brilliant team making our history to evolve the commerce industry. fabric is the next-generation commerce platform that is designed to provide the commerce services customers expect so they can build world-class experiences, anywhere.

fabric is on a mission to revolutionize commerce for everyone, and we empower businesses that are striving to deliver commerce that drives conversion and customer outcomes. Leading retailers, including Chico’s, Brooklinen, and Ashley’s Furniture, trust fabric to run their modern commerce business. Headquartered in San Francisco, fabric was founded in 2017 by a group of industry veterans determined to bring the same technical principles found at Amazon to retail.

No matter what field you are in, fabric has exciting opportunities for people passionate about making a difference and skilled at what they do!

Here are four questions you should ask yourself:

1. Do I believe in fabric's mission?
2. Am I eager to build cool things?
3. Am I excited to collaborate with brilliant people?
4. Am I motivated to disrupt e-commerce?

If the answer is yes, we want to talk to you!

Where we hire:

Canada (Toronto & Vancouver)

Your next career:

At fabric, we're building the future of commerce with AI-powered, data products that help merchants make and save more money. We’re looking for a Principal AI/ Machine Learning Engineer to lead the development of data products — from raw data to production grade solutions.

This is a high-impact, hands-on role (reporting directly to CPTO) for someone who thrives in fast-paced startup environments, has built and scaled multiple data products, and is passionate about taking ideas from zero-to-one while influencing the long-term technical direction of AI/ML at fabric.

Your Responsibilities:

1. Own AI/ML initiatives end-to-end: Frame problems, design solutions, build/train models, test and deploy to production.
2. Develop production-grade ML systems: Architect and implement pipelines for training, testing, serving, monitoring, and retraining.
3. Apply a wide range of techniques: Deep learning, reinforcement learning, supervised/unsupervised learning, linear/non-linear optimization, and probabilistic modeling.
4. Build scalable, intelligent data products: like recommendation engines, forecasting, fraud detection, search, NLP, categorization, personalization, and operations optimization.
5. Lead MLOps efforts: Establish and maintain infrastructure and tooling for quick experimentation, validation, and deployment.
6. Collaborate cross-functionally: Work with engineering & product teams to embed intelligence into user-facing products.
7. Drive innovation: Stay on top of new research and industry trends to inform AI/ML roadmap and technology choices.

What you bring to the table:

1. 8+ years in AI/ML role, with high-growth startup — you’ve built and launched multiple data products from scratch.
2. Track record of building and scaling ML solutions in real-world applications, such as recommendations, forecasting, fraud detection, clustering, and categorization.
3. Full-stack ML expertise across:
1. Data Engineering - feature engineering/ store, distributed data processing
2. Modeling - deep learning, classical ML, RL, unsupervised learning
3. MLOps - deployment, monitoring, CI/CD, infrastructure
4. Strong programming skills using Spark, Python, TensorFlow/PyTorch, MLFlow, Airflow, Docker, Kubernetes, etc.
5. Passion for building usable, scalable systems—not just research or models.
6. Advanced degree (PhD or MS) in CS, ECE, Statistics, Econometrics, Physics, or relevant industry experience.
7. Strong communication and leadership skills with the ability to mentor others and influence technical direction.

The base salary for this role will be between CAD $170K to 225K.

The annual base salary range for this full-time position reflects the minimum and maximum target salaries for the position across all Canada locations. Actual pay may vary, depending on qualifications, experience and location. In addition, this role may be eligible for an annual performance bonus, equity options, and company benefits (your recruiter can share more details during the hiring process). Final offer amounts may vary from the amounts listed above.

What we bring to the table:

1. Competitive compensation packages
2. PTO and Holiday plans
3. Benefits packages which include Medical, Dental, Life, and Vision
4. Wellness & Technology Programs
5. Retirement Savings Plan
6. Fast-paced, fun and collaborative environment
7. A team invested in you both personally and professionally

#LI-Remote