Senior Cloud Engineer, Computer Vision Infrastructure

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

Key Responsibilities May Include:

• Design, orchestrate, and maintain scalable cloud infrastructure, working with engineers to automate processes and improve efficiency.
• Collaborate with Innovation Squads, Product Success, and other teams to maintain fast, reliable, and resilient CI/CD pipelines, empowering engineers to self-service their infrastructure needs.
• Support the development, testing, and maintenance of disaster recovery scenarios to ensure system availability and business continuity.
• Develop and deploy automated tools that enhance the developer experience, simplifying infrastructure management and deployment processes.
• Monitor performance, capacity, and availability of systems and infrastructure, working cross-functionally to troubleshoot and resolve platform-related issues.
• Create and maintain technical documentation, ensuring it is fit for use in design reviews, incident response, and support processes.
• Ensure best practices in cloud security, governance, and compliance are implemented across all cloud platform services.
• Stay up-to-date on emerging cloud technologies and trends, applying knowledge to continuously improve the scalability and performance of cloud platforms.

POSITION PURPOSE

Cloud Engineers set up, operate, develop, evolve, and maintain cloud-centric platform(s) including IoT, Customer Solution Delivery, Data Science Environments and Software Delivery, as well as satellite tools and environments (file storage, databases, frameworks for data streaming, eventing, machine learning and big data, data science notebook technologies, and container orchestration tooling, taking into account reliability, monitoring and cost

SCOPE

• Global 

MAJOR / KEY ACCOUNTABILITIES

• Responsible for experimenting with and implementing machine learning frameworks for data science/machine learning development and operations

• This person will be dedicated to the Computer Vision Data Science team to support serialization related machine learning infrastructure

• Responsible for learning and operating new data science frameworks and technologies and exploring their viability for current and planned projects

• Responsible for learning and operating data storage frameworks and technologies and exploring their viability for current and planned projects

• Responsible for rigorous testing of framework robustness and scalability

• Will contribute to data science teams and the engineering teams discussions, providing insight as needed on other team member’s current approaches and methods as well as on tools and data repositories.

• Liaise with Cloud Team (Global IT) to understand corporate-wide cloud standards and policies and ensure compliance

• Supporting Serialization and Asset digitization programs across

• Responsible for the Continuous Integration and Deployment pipelines to support data science learning and production software delivery

• Responsible for contributing to capability building of the Cloud Engineering team, including researching and staying up-to-date on best practices e.g. GitOps, IaC (infrastructure as code).

MEASURES

• Successful roll out, development and continuous evolution and operation of cloud-based data science and machine learning platforms, both for research & development and for continuous operation

• Effective support of data science projects

• Reliability of systems

• Adoption of new systems and data science approaches

AUTHORITY / DECISION MAKING

• Data science and machine learning frameworks: selection and implementation

• Tooling selection and implementation

• Working autonomously in a highly matrixed organization

KEY CONTACTS

Internal:  Digital Data Sciences and Application Development team, Digital Product Teams (PM), Software Engineering Teams, Technology Services Cloud Engineering

External:  Potential vendors (e.g. for data science or monitoring tools)   

QUALIFICATIONS

• BS degree in Data Science, Computer Science, Engineering, Math, Statistics, Physics, or similar formal training or equivalent 

Desirable:

• Proven experience with looking after data science environments

• Proven experience with looking after data storage systems with high availability and database tuning

• Proven experience with FinOps and being able to optimize spend for CE impact

• Experience with working with IoT and Edge interaction with the Cloud

EXPERIENCE

• 5 years relevant experience in Cloud Engineering or adjacent fields

• Installed, operated, and managed several data science and machine learning frameworks, or developed own data science methodologies

• Experience with Continuous Integration and Continuous Deployment

• Experience operating, optimizing, querying, and administering databases (such as Iceberg, Postgres, Patroni, DuckDB, TimescaleDB, etc.)

• Comfortable using and working in a polyglot computer language environment (Python, Go, Julia etc.)

• Experience with Amazon Web Services (S3, EKS, ECR, EMR, etc.)

• Experience with containers and orchestration (e.g. Docker, Kubernetes)

• Experience with Big Data processing technologies (Kubeflow, Spark, Hadoop, Flink etc)

• Experience with interactive notebooks (e.g. JupyterHub, Databricks)

• Experience with Git Ops style automation

• Experience with *ix (e.g, Linux, BSD, etc.) tooling and scripting

• Participated in projects that are based on data science methodologies, and/or physical experiments, or statistical analysis – especially in a data engineer and dev ops capacity.

SKILLS AND KNOWLEDGE

• Knowledge of major data science and dev ops frameworks and methods

• Very strong analytical skills and systems thinking

• Strong programming skills in addition to operational skills a plus (ideally in one or more of the following languages: Python, Go, Julia, or C/C++)

• Attention to big picture and details

Remote Type

Skills to succeed in the role

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 recruitment@brambles.com.