استخدام Senior Machine Learning Engineer (قزوین-دورکاری)
شرح موقعیت شغلی
Senior Machine Learning Engineer
Company: Ezhoosh
Job Description
We are looking for a Senior ML Engineer to design, build, and optimize machine learning models and pipelines powering production systems at Ezhoosh. The ideal candidate brings deep hands-on experience across the ML lifecycle, with particular strength in recommender systems, deep learning, LLM agents, and MLOps practices.
Responsibilities
- Design, train, and iterate on ML and deep learning models for recommendation, ranking, and personalization use cases.
- Architect and maintain end-to-end ML pipelines.
- Set up and optimize scalable data processing and ML workflows.
- Build and maintain robust MLOps infrastructure.
- Collaborate with data engineers to ensure data quality, build feature stores, and prepare datasets for model training and inference.
- Evaluate and benchmark model performance, run offline and online experiments, and drive continuous improvement of model accuracy and efficiency.
- Optimize model serving infrastructure for latency, throughput, and cost-effectiveness.
- Partner with product and business stakeholders to translate requirements into well-scoped ML solutions.
- Document model architecture, assumptions, performance characteristics, and known limitations.
- Stay current with advances in recommendation systems, deep learning, and AI services, and propose improvements to existing approaches.
Requirements
- 4+ years of hands-on experience in machine learning engineering.
- Strong proficiency in Python and core ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn, XGBoost, etc.).
- Hands-on experience designing, developing, and deploying LLM Agents and AI orchestration systems.
- Solid experience with deep learning — architecture design, training, hyperparameter tuning, and deployment of neural network models.
- Proven experience designing and deploying recommender systems.
- Strong MLOps skills and a solid understanding of the full ML lifecycle.
- Hands-on experience with containerization and orchestration in production environments.
- Proficiency with SQL and experience working with both structured and unstructured data sources.
- Strong problem-solving skills with an emphasis on scalability and performance optimization.
Bonus Points (Plus)
- Hands-on experience with AWS SageMaker and the broader AWS ML ecosystem.
- Practical experience setting up data processing and ML workflows specifically on AWS.
- Experience architecting cloud-based ML infrastructure on AWS.
مهارتهای مورد نیاز
- Python
- Machine learning
- یادگیری ماشین
حداقل سابقه کار
- سه تا شش سال
جنسیت
- مهم نیست
وضعیت نظام وظیفه
- مهم نیست