Machine Learning Engineer
Saxon Global Inc
We're partnering with a client to hire ML Search Engineers who are excited about building a modern, machine learning-driven search platform that powers intelligent product discovery across a large e-commerce ecosystem.
This opportunity sits within a newly formed Search Engineering team, working closely with senior ML leadership and an Innovation organization. You'll help take an existing ML search proof of concept and evolve it into a scalable, production-ready system used across customer-facing and internal platforms.
This is a hands-on engineering role focused on building, operating, and improving ML systems in production - not research-only work.
What You'll Be Doing:
This opportunity sits within a newly formed Search Engineering team, working closely with senior ML leadership and an Innovation organization. You'll help take an existing ML search proof of concept and evolve it into a scalable, production-ready system used across customer-facing and internal platforms.
This is a hands-on engineering role focused on building, operating, and improving ML systems in production - not research-only work.
What You'll Be Doing:
- Implement ML -driven search components designed by a Search Architect
- Build and maintain Python-based ML pipelines for embeddings, inference, and relevance
- Work with vector search and similarity matching to enable intent-based product discovery
- Support GPU-based workloads for model computation and inference
- Participate in MLOps workflows, including deployment, monitoring, retraining, and maintenance
- Refresh and rerun embeddings as product data evolves
- Collaborate with Architecture, Innovation, and Engineering teams to deliver production ML systems
- Debug, optimize, and improve search performance, reliability, and relevance
- Contribute to ongoing enhancements as the search platform grows
- Strong Python development experience (primary language)
- Experience building or supporting machine learning pipelines in production
- Understanding of the ML lifecycle (training, inference, retraining, monitoring)
- Familiarity with MLOps principles
- Experience working with large datasets and model outputs
- Comfortable working hands-on in evolving environments with ambiguous requirements
- Strong problem-solving and collaboration skills
- Experience with vector databases or similarity search
- Exposure to embeddings, semantic search, or recommendation systems
- Experience supporting GPU-based workloads
- Cloud ML experience (AWS, GCP, or Azure)
- Background in e-commerce search, discovery, or relevance systems
- Work on real-world ML systems used at scale
- Join a team early as a core contributor to a growing search platform
- High visibility work with meaningful technical impact
- Strong collaboration with senior ML and innovation leaders
Vacancy posted 8 hours ago
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