Website Tabby
Description
Job Title: ML Engineer
We are looking for a Senior ML Engineer to join our Search & Personalization team. While our team is responsible for building end-to-end ML solutions, your primary focus will be on the engineering side of the ML product lifecycle—ensuring seamless CI/CD processes, scalable infrastructure, and robust product ionization of ML models (both offline and online).
Our ML models power key marketplace features, including Search, All-Stores, and the main page of the marketplace. Our mission is to transform Tabby into more than just a BNPL platform—by connecting users with their aspirations.
Responsibilities
- Own the engineering backbone of our ML lifecycle, ensuring reliable and scalable model deployment.
- Develop and optimize Airflow DAGs for offline model training and inference.
- Design and implement best practices for ML model registry, experiment tracking, and CI/CD pipelines.
- Build and maintain robust monitoring for both offline jobs and online services.
- Develop automated testing frameworks, covering data quality, integration, and load testing.
- Collaborate with Applied Scientists to transition offline experiments into production-ready ML products.
- Work closely with Backend Engineers to integrate ML models seamlessly into production systems.
- Develop and optimize scalable Python services for model serving and data pipelines.
Skills, Knowledge & Expertise
- 3+ years of experience as an ML Engineer.
- Strong proficiency in ML engineering tools, including:
- W&B / ClearML / MLflow / DVC
- GitLab CI/CD, Docker, Kubernetes, Airflow
- FastAPI for serving ML models
- Hands-on experience with cloud platforms (preferably GCP).
- Deep understanding of ML system design best practices.
- Familiarity with ML/DL Python stack: PyTorch, Pandas, Scikit-learn, Transformers, OpenAI APIs.
- Solid experience in SQL and working with structured data.
- English proficiency: B1+ (intermediate or higher).
Bonus Skills (Nice to Have)
- Experience designing and scaling high-load Python services.
- Background in automated testing (data quality, integration, load testing).
- Experience with real-time ML model deployment and inference.
- Knowledge of model optimization techniques: quantization, distillation, pruning.
- Familiarity with Go or other backend programming languages.
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To apply for this job please visit tabby.pinpointhq.com.
ML Engineer at Tabby, Remote (Global)
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