Description
We are looking for a freelance contractor to work with us as a Senior ML Engineer.
In this role, you will work alongside our search expert, data scientist, and backend engineers to build and produce machine learning models that enhance our search relevancy and advertising effectiveness. As we migrate to Databricks as our data warehouse, you will be crucial in establishing ML best practices, implementing scalable model pipelines, and educating the team on leveraging Databricks' ML capabilities. This position requires technical ML expertise and strong engineering skills to help us build a state-of-the-art search system that treats relevancy as a first-class priority.
Must have:
- Proven experience building and productionizing ML models for large-scale applications, with a focus on search relevancy or recommendation systems
- Experience implementing ML infrastructure components such as feature stores, model registries, and automated deployment pipelines
- Strong software engineering fundamentals with an emphasis on clean code, testing practices, and CI/CD for machine learning models
- Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or scikit-learn
- Experience with ML model lifecycle management, including experiment tracking, versioning, and performance monitoring
- Expertise in scaling ML systems to handle production workloads with high throughput and low latency
- Strong communication skills to effectively collaborate with cross-functional teams and educate colleagues on ML best practices
- Experience with Agile methodologies and iterative development of ML features
Start: Immediately
Duration: Until the end of the year
Place: fully remote
Working hours: 40 hours per week, full-time
Language: English
In this role, you will work alongside our search expert, data scientist, and backend engineers to build and produce machine learning models that enhance our search relevancy and advertising effectiveness. As we migrate to Databricks as our data warehouse, you will be crucial in establishing ML best practices, implementing scalable model pipelines, and educating the team on leveraging Databricks' ML capabilities. This position requires technical ML expertise and strong engineering skills to help us build a state-of-the-art search system that treats relevancy as a first-class priority.
Must have:
- Proven experience building and productionizing ML models for large-scale applications, with a focus on search relevancy or recommendation systems
- Experience implementing ML infrastructure components such as feature stores, model registries, and automated deployment pipelines
- Strong software engineering fundamentals with an emphasis on clean code, testing practices, and CI/CD for machine learning models
- Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or scikit-learn
- Experience with ML model lifecycle management, including experiment tracking, versioning, and performance monitoring
- Expertise in scaling ML systems to handle production workloads with high throughput and low latency
- Strong communication skills to effectively collaborate with cross-functional teams and educate colleagues on ML best practices
- Experience with Agile methodologies and iterative development of ML features
Start: Immediately
Duration: Until the end of the year
Place: fully remote
Working hours: 40 hours per week, full-time
Language: English