CHEP helps move more goods to more people, in more places than any other organization on earth via our 347 million pallets, crates and containers. We employ approximately 13,000 people and operate in 60 countries. Through our pioneering and sustainable share-and-reuse business model, the world’s biggest brands trust us to help them transport their goods more efficiently, safely and with less environmental impact.
What does that mean for you? You’ll join an international organization big enough to take you anywhere, and small enough to get you there sooner. You’ll help change how goods get to market and contribute to global sustainability. You’ll be empowered to bring your authentic self to work and be surrounded by diverse and driven professionals. And you can maximize your work-life balance and flexibility through our Hybrid Work Model.
Job Description
The Machine Learning Engineer will be responsible for developing machine learning capabilities and systems to support Asset Productivity. This will involve running tests and experiments on how we can identify in-efficiencies or anomalies in pallet declarations and flows. Any successful experiments will need to be productionised and automated to support Stakeholders.
Key Accountabilities
- Develop robust, scalable, and reliable Machine Learning solutions that support Asset Productivity.
- Utilise CI/CD best practices to ensure successful deployment of ML models.
- Advocate for continuous improvements to ML products through adoption of MLOps principles.
- Work in an agile and iterative way with product owners, data scientists, and engineers to collaborate on projects.
Essential Skills:
- Bachelor’s degree in computer science, Statistics, or other technical degree.
- Solid understanding of ML concepts, including supervised and unsupervised learning, feature engineering, and model evaluation.
- Strong foundation in mathematics and statistics, including linear algebra, probability, and optimisation techniques.
- Proficiency in Python and experience with ML libraries such as Scikit-learn, TensorFlow, or PyTorch.
- Experience developing efficient, reusable, and maintainable code.
- Familiarity with version control systems for collaborative development and code management.
- Basic knowledge of cloud platforms such as AWS.
Preferred Skills:
- 1+ years of experience in ML, data science, or software development.
- Proven ability to develop and implement ML models in production.
- Familiarity with ML lifecycle tools, e.g. MLFlow.
- Experience with A/B test design, implementation, and monitoring.
- Strong interest in GenAI, specifically an understanding of its core concepts, architectures, and practical applications.
- Experience using the Databricks platform for end-to-end ML development, including data processing, model training, and deployment.
Remote Type
Hybrid Remote
We are an Equal Opportunity Employer, and we are committed to developing a diverse workforce in which everyone is treated fairly, with respect, and has the opportunity to contribute to business success while realizing his or her potential. This means harnessing the unique skills and experience that each individual brings and we do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state, or local protected class.
Individuals fraudulently misrepresenting themselves as Brambles or CHEP representatives have scheduled interviews and offered fraudulent employment opportunities with the intent to commit identity theft or solicit money. Brambles and CHEP never conduct interviews via online chat or request money as a term of employment. If you have a question as to the legitimacy of an interview or job offer, please contact us at [email protected].
Top Skills
What We Do
CHEP is a global leader in managed, returnable and reusable packaging solutions, serving many of the world's largest companies in sectors such as consumer goods, fresh produce, beverage and automotive. CHEP’s service is environmentally sustainable and increases efficiency for customers while reducing operating risk and product damage. CHEP’s 7,500-plus employees and 300 million pallets and containers offer unbeatable coverage and exceptional value, supporting more than 500,000 customer touch-points in 49 countries. Our customer portfolio includes global companies and brands such as Procter & Gamble, Sysco, Kellogg's, Kraft, Nestlé, Ford and GM. CHEP is part of Brambles Limited. For more information, visit www.chep.com.
Reliability. Flexibility. The success of your business depends on both. With CHEP, you can be confident that you’ll get the equipment you need, when and where you need it. Our scale is unmatched, with more than 110 million pallets and over 530 service centers across North America. So you no longer need to worry about seasonal peaks or unexpectedly high demand.
With our broad array of solutions and our pragmatic, roll-up-your-sleeves know-how, we give our consumer goods customers the platforms, the quality, the supply and the support they need to make more money on every unit load. Because everything just works better.
