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Senior Machine Learning Engineer
2 weeks ago
We are modernizing our forecasting capabilities through a cutting-edge platform.
As a highly skilled Senior Data Scientist / ML Engineer, you will design and operationalize advanced forecasting solutions at scale. This role combines hands-on machine learning with solid software engineering practices to deliver robust, scalable, and transparent forecasting capabilities.
Key Responsibilities:
- Design, build, and deploy production-grade forecasting models using distributed training frameworks.
- Develop end-to-end machine learning pipelines for data ingestion, feature engineering, model training, and deployment.
- Build probabilistic models to quantify forecast uncertainty and provide actionable insights.
- Write clean, modular, object-oriented code following best practices and implement MLOps best practices including model versioning, monitoring, and CI/CD.
- Collaborate with cross-functional teams (engineering, product, strategy) to align solutions with business needs and drive growth.
Requirements:
- 3–6 years of relevant experience in Data Science / ML Engineering.
- Strong proficiency in Python and core libraries such as pandas, numpy, scikit-learn.
- Hands-on experience with deep learning frameworks (preferably PyTorch).
- Experience working in cloud environments (e.g., Databricks, AWS, GCP) for large-scale data processing.
- Proven ability to build scalable, production-grade ML pipelines and drive business outcomes.
- Excellent problem-solving, communication, and collaboration skills.
Education:
MS or BS in CS or related from a top university.
As a valued member of our team, you will have opportunities to grow and develop your skills in a dynamic and supportive environment. We offer competitive compensation and benefits packages, as well as a collaborative and inclusive work culture.
