Senior Machine Learning Engineer [Decisions]

Join our fast-growing ML Solutions squad within the Global AI team and help shape the future of machine learning at HelloFresh! We’re on a mission to build a cutting-edge MLOps platform and scale ML-powered solutions across the company.

As part of the Global AI team, you’ll work cross-functionally with Data Scientists, ML Engineers, and Data Engineers to design, deploy, and maintain best-in-class data products that enhance the HelloFresh user experience. We thrive on tackling complex challenges, automating workflows, and crafting scalable ML solutions using the latest AI, big data, and cloud technologies (AWS, Spark, Prefect, Databricks, and more).

If you're passionate about building robust ML systems, enjoy working in a dynamic and collaborative environment, and want to make a real impact with AI, we’d love to hear from you!

You are...

• Develop and improve Machine Learning solutions to help our data scientist productionize models across the full customer experience (web, marketing, logistics, …)
• Enable data scientists to easily provision clusters to train models on huge datasets and deploy feature engineering pipelines.
• Deploy and monitor models in production (e.g. building artifacts, measuring model drift, integrating with CI/CD, etc ...)
• Support and consult with data scientists regularly to ensure a high adoption rate of our solutions across HelloFresh and promote best practices
• Close the loop with human interaction: automating measurements and feedback gathering to iterate on our solutions

You have...

• Experience deploying ML models to production
• Previous commercial experience building machine learning models or developing MLOps solutions
• Knowledge of basic modeling techniques for classification, regression, or time-series forecasting (e.g. Logistic Regression, Regularization, Gradient Boosting, Random Forests, etc…).
• Demonstrated experience building software with Python and proficiency with data and ML-related open-source libraries such as Pandas, Scikit-Learn, Catboost/XGboost, TensorFlow.
• Demonstrated experience implementing good software engineering practices (e.g. version control, code modularity, testing, …)
• Experience working with Cloud infrastructure (e.g. AWS, GCP, Azure)
• Experience with Infrastructure as Code (e.g. Terraform or similar)
• Experience with Deep Learning techniques is a plus
• Experience with Apache Spark is a plus

You'll get...

• Box Discount - Amazing discounts on 1 box per week! 75% discount on weekly HelloFresh and Chefs Plate meal kits AND 50% off weekly Factor meal box.
• Health & Wellness - Health & Dental benefits from day 1, a Health Spending Account, unlimited access to the Headspace app to meet your self-care needs, and 25% discount on GoodLife fitness memberships!
• Vacation & PTO - Time off is also an important part of self-care! We offer generous vacation and PTO to help you create a good work-life balance. 
• Family Benefits - A parental leave top-up program for expectant parents.
• Growth & Development - We support your career progression and invest in your continued learning through experiences and initiatives owned by our dedicated L&D team
• Work Hard & Have Fun - From team socials to engaging company days, you’ll have plenty of opportunity to experience the fun!
• Diversity & Inclusion Initiatives - With impactful ERG’s like FreshPride, Women Empowered and LIMES, we are committed to our diversity, equity & inclusion efforts.
• Food Puns - this one is kind of a big dill if you haven’t already noticed. We even have some punny meeting room names!

Flexible Hybrid Approach

At HelloFresh, we know that flexible work arrangements are essential in enabling you to do your best work, while balancing your personal and life needs. Offering remote work flexibility, along with the opportunity to interact and collaborate in the office are all a part of creating a great employee experience. 

To meet these needs, we are pleased to provide Flexible Hybrid work. Flexible Hybrid is a people-first approach that is based on choice, trust, personalization, and empowers teams to choose when and how often they work from the office and work from home, in addition to team days and company days. This means a minimum of 2 days in office per week, with most teams in office between 2-3 days a week.

#LI-HYBRID

#Decisions