Position Background:  

In the Go To Market Analytics Centre of Excellence our mission is to deliver impact by building machine learning products to optimize pricing and marketing investments and provide guidance to our sales organization. The products we are building are of high value to the company, with the ambition to affect the pricing decisions and marketing investments for all of HP products, globally and across all distribution channels, utilizing advanced analytics, machine learning and AI. 

To get there, we are looking for a ML Cloud Engineer to implement best engineering practices and to turn data from a raw resource into structured, scalable, high-quality, and compliant fuel feeding our AI-powered products and solutions. 

Please note that it's a fixed-term role with a 12 month contract. Extension to permanent position is possible but not guarantee.

What makes us stand out: 

Best in class Technologies. 

Diverse learning opportunities. 

Super collaborative environment and international experience. 

About you: 

Curiosity, explore new topics 

Rigorous, synthetic, methodical 

Self-starter with intellectual curiosity 

Team lead with a balance profile between Computer Science and ML Cloud Engineering 

Responsibilities:  

Design and implement CI/CD pipeline architectures in all stages (design, analysis, coding, testing and pipeline integration). 

Usage of several Python, Cloud and ML tools to deploy ML models into Development, Stage and Production environments. 

Monitor product health, performance and business impact and act accordingly when requirements are not met. 

Work with business stakeholders with diverse backgrounds and own team-level objectives, building and managing relationships through the organization. 

Own operational excellence objectives targeting reliability, quality, and release cadence, while perfecting operational economies of scale through extreme automation. 

Ensure compliance of code standardization, systems, and products with infrastructure policies (incl. privacy), architecture, security and quality guidelines and standards. 

Co-design and lead architecture evolution activities through innovation and adoption of new technologies. 

Collaborates and communicates with project team regarding project progress and issue resolution. 

Provides guidance and mentoring to less experienced staff members. 

Job Requirements: 

Bachelor's or Master's Degree in Computer Science, Information Technology, Engineering or equivalent, demonstrated through work experience, journal and/or conference publications or open-source projects. 

5+ years of relevant experience in software development, design and fundamentals. 

Proficiency (4+ years) in the Python language. Extensive experience with Python programming, including writing and maintaining Python scripts for automation, data processing, and integration within CI/CD pipelines. Ability to develop and deploy Python-based applications in containerized environments. 

Proficiency with Docker (2+ years): Strong experience in creating, managing, and optimizing Docker containers. Ability to write Docker files to build and maintain images for various environments. 

Proficiency in Test-Driven-Development (TDD), integration testing, unit testing and be able to ensure quality code at delivery time, such as review Pull-Requests in a standardized manner. 

Expertise in Cloud Based Architectures (2+ years). Demonstrated knowledge of building and developing architectures and pipelines within the cloud environment. Preferred AWS knowledge (DynamoDB, S3, RDS, ECR, Lambda, EC2…). 

CI/CD Expertise using GitHub Actions: Hands-on experience in setting up and managing continuous integration/continuous deployment (CI/CD) pipelines using GitHub Actions. Proficiency in configuring workflows that incorporate Docker for building, testing, and deploying applications. 

Collaborative Development: Ability to work in a collaborative environment, using Docker and GitHub to facilitate smooth integration and deployment processes across development teams. 

Documentation and Best Practices: Strong ability to document processes, workflows, and best practices for Docker, Python, and CI/CD pipeline management. 

Experience in mentoring and assisting other teams in adopting these best practices, ensuring consistency and efficiency across the organization. 

Excellent English communication skills, both written and verbal. 

Nice to have 

Having AWS Certifications is a bonus. 

Previous experience in ML Operations is a bonus. 

Experience in ML tools such as Databricks, MLFlow, Python libraries such as Pandas or Polars, Grafana, OpenSearch... 

Previous experience in Databases and SQL. 

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