About the Client

Our client is a fast-growing technology company focused on transforming how small businesses manage their operations. They are known for their user-centric approach and commitment to delivering intuitive, high-impact digital solutions. The team values innovation, collaboration, and rapid iteration, with a strong emphasis on leveraging data and machine learning to enhance both customer experiences and internal decision-making. You'll be contributing to a dynamic environment where your work will directly support real-world outcomes across a widely adopted platform.
As a Machine Learning Engineer contractor you'll be able to help design, build, and deploy machine learning solutions that directly support customer experiences and internal decision-making.

Project details

This role is hands-on and highly collaborative, with a focus on applied modeling, data exploration, and production-grade ML engineering using Google Cloud, Platform (GCP) and Vertex AI.

Your Team

You’ll partner with Data Engineers, Product Managers, and other stakeholders to deliver ML workflows from prototype to deployment. This is a great opportunity for someone experienced in GCP-native ML development looking to make an impact in a fast-moving team.

What's in it for you

• Interview process that respects people and their time
• Professional and open IT community
• Internal meet-ups and resources for knowledge sharing
• Time for recovery and relaxation
• Bright online and offline events
• Opportunity to become part of our internal volunteer community

Responsibilities

• Design and build ML models using Python and common libraries (e.g., scikit-learn, XGBoost). Develop and productionize ML workflows using Vertex AI (e.g., training pipelines, batch predictions). 
• Explore and transform data using BigQuery, leveraging a shared feature store. Package and deploy models with our internal MLOps tooling, integrated with GCP infrastructure. 
• Monitor deployed models and support continuous improvement through retraining and tuning. 
• Participate in A/B testing and experiment analysis (e.g., champion/challenger models). 
• Collaborate with Data Engineers to ensure clean, reliable data and scalable infrastructure. 
• Follow best practices in software development (CI/CD, version control, automated testing).

Skills

• Strong Python and SQL skills
• Direct experience with Vertex AI and GCP ML infrastructure
• Proven track record of building and deploying ML models to production
• Familiarity with ML frameworks (e.g., scikit-learn, XGBoost, TensorFlow)
• Understanding of MLOps practices (e.g., model packaging, pipeline orchestration)
• Comfortable with CI/CD, version control, and writing maintainable, testable code
• Experience with experiment design and evaluation

Nice to Have

• Exposure to LLMs, prompt engineering, and tools like LangChain or Google ADK
• Experience working with feature stores or real-time ML pipelines
• Familiarity with batch and online prediction use cases in Vertex AI