About Brenntag
Brenntag is the leading global distributor of chemicals and ingredients, committed to connecting customers and suppliers within networks. We add value for our customers and partners every step of the way : through our product knowledge, innovation, and sustainable solutions, combined with our passion for service excellence and commitment to safety..
Headquartered in Essen, Germany and with more than 17,500 experts at about 600 locations in 72 countries, our two global divisions, Brenntag Essentials and Brenntag Specialties, offer a full range of industrial and specialty chemicals and ingredients. Therefore, our clients and partners can count on us for global reach combined with local agility and execution.
As an employer, we embrace diversity and foster a sense of community and collaboration in an environment where employees are encouraged to share ideas and work together. We engage our employees in the company's mission for collective success, by building long-term stability and safety through trust and clarity across the organization. We believe in empowering our employees to reach their full potential and shape the future.
For more information, please visit www.brenntag.com
Responsibilities
- Integrate machine learning models with operational applications and tools
- Design and build APIs and software libraries that support the integration of models
- Manage, deploy models at scale that solve business problems
- Optimize machine learning models through hyperparameter tuning and feature engineering to better solve defined business problems
- You will be part of the analytics engineering lifecycle, including designing distributed systems, writing production-level code for data sciences models, conduct code reviews while working alongside our data engineering and infrastructure teams.
- Support the investigation of new software packages / tools, APIs, and algorithms to deliver quality analytics and machine learning at scale
Qualifications
Bachelor's degree in computer science, mathematics, statistics, economics, engineering or related field3 to 5 years of experience in Machine Learning EngineeringExperience working with DatabricksExperience with GitLab pipelinesCompetency with infrastructure as code (e.g., Terraform with AWS)Experience with MLOps & model lifecycle management using DatabricksExperience with development & deployment of large scale Machine Learning Project 2+ years of experience with MLOpsDevelop & test large scale machine learning applications with team of data scientists and engineersExperience with various programming and scripting languages (Python, Bash, C++)Extensive knowledge of machine learning evaluation metrics and best practicesCollaborative individual who thrives in a team environment, specifically within a matrix organizationCreative problem solver and innovatorWhat makes' working as MLE at Brenntag great?
Opportunity to develop high impact & real value generating machine learning applications.What you can expect from us :
Unique greenfield environment to drive change in a global businessHave fun working in the passionate and experienced teamOpportunity to present your ideas and learn from others at our Product Engineering GuildHybrid workplace modelCool office with canteen, Friday beers and Nintendo SwitchCompetitive compensation packageInternational teamFriendly and supportive colleaguesBrenntag provides equal employment opportunities to qualified applicants and employees of all backgrounds and identities to create a workplace where difference is valued because it forms a resilient and more innovative organization. We do not discriminate on the basis of age, disability, gender identity, sexual orientation, ethnicity, race, religion or belief, parental and family status, or any other protected characteristic. We welcome applications from women, men and non-binary candidates of all ethnicities and socio-economic backgrounds.