AI Engineer

Key Skills

Aartificial intelligence, Agile methodologies, Azure, Cloud computing, Continuous Integration & Continuous Delivery - CI/CD, Data Analytics, Data Modeling, DevOps, Effective communication skills, Github, Google Cloud Platform (GCP), JIRA, Machine learning techniques, PyTest, Python Programming, SQL, Writing

Job Description

Are you a ML / AI Engineer, fluent in Python and SQL, who wants to work on scaling and operationalization of large-scale use cases to drive significant business impact?

Do you want to work on modern cloud technology stack in Azure and GCP – hyperscale cloud providers?

The AI Engineering at Procter & Gamble is responsible for operationalizing and supporting AI use cases using products that embed Machine Learning pipelines deployed to e.g. Google Cloud Platform, that utilize Big Query, Kubeflow and Python language, and is looking for AI Platform Engineer with a passion to creatively solve scalability, deployments and development problems in our team.

The AI Engineering Team at Procter & Gamble is responsible for products that embed Machine Learning pipelines deployed to Google Cloud Platform that utilize Big Query, Kubeflow and Python language -> and is looking for an experienced AI Engineer with a passion to creatively solve scalability, deployments and development problems in our team.

Responsibilities

• Works on advanced analytics use cases together with Data Scientists, Analysts, peer AI Engineers; engages in proof of concepts and experiments together to deliver new analytical algorithms and applications
• Prepares data models and quality checks, optimizes analytical solutions at scale
• Designs and develops applications that source data from various systems, programming in Python and SQL
• Supports solutions in multi-cloud environments and services – in Azure (e.g. Databricks, Azure ML, AKS, ADF) and / or in GCP (e.g. Composer, BigQuery, GKE, Kubeflow)
• Operates according to DevOps practices, Agile (Jira), uses CI/CD (GitHub Actions), increases reusability of code and design patterns from internal code libraries
• Operationalizes Machine Learning models as integral element of IT solutions & business process.
• Implements best Platform Engineering practices to make cloud infrastructure “invisible” for data scientists and model developers
• Troubleshoots infrastructure related issues to enable most critical Artificial Intelligence products at P&G
• Proactive incident detection systems based on multiple data sets, real-time data stream analyses
• Crafts and develops proof of concept or prototypes for new features or solutions, suggests and implements architecture improvement, and has responsibility for strengthening DevOps best practices within AI Engineering by coaching/teaching others

We offer

• Fortune 50-sized projects and access to world leading IT partners and technologies from day one.
• Coaching programs, training and support for certifications.
• Opportunity to change role every few years to be in the best place for you and best for P&G
• Competitive starting salary and benefits program

Job Qualifications

Required

• A Bachelors or Master’s degree in Computer Science, Software Engineering or related field
• 2+ years of proven experience in Python & SQL, data modelling, design, development, and deployment of Data and Analytics products

Preferred

• Experience in Agile, CI/CD and DEVOPS methodologies – knowledge of using appropriate tools, e.g. Jira, GitHub Actions
• Testing (e.g. PyTest) & mocking, static code analysis (e.g. Sonarqube), source control management tools (e.g. GitHub)
• GCP/Azure cloud infrastructure knowledge (including load balancing, autoscaling, firewalls, authentication)
• Experience with AI/ML products and model pipelines and deployment processes
• Logging and monitoring technologies
• Strong written and verbal communication in English.