
Machine Learning Expert
2 weeks ago
Job Overview
We are seeking a highly skilled Senior Data Scientist / ML Engineer to design and operationalize advanced forecasting solutions at scale.
This role blends hands-on machine learning with solid software engineering practices to deliver robust, scalable, and transparent forecasting capabilities.
- Design, build, and deploy production-grade forecasting models
- Develop end-to-end machine learning pipelines for data ingestion, feature engineering, model training, and deployment
- Build probabilistic models to quantify forecast uncertainty
- Write clean, modular, object-oriented code following best practices
- Implement MLOps best practices including model versioning, monitoring, and CI/CD
- Work with distributed training frameworks for scalable model development
- Collaborate with cross-functional teams (engineering, product, strategy) to align solutions with business needs
- Work with cloud-based environments (e.g., Databricks, AWS, GCP) for large-scale data processing
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 with distributed training and large-scale datasets
- Proven ability to build scalable, production-grade ML pipelines
- Familiarity with MLOps practices (CI/CD, monitoring, retraining pipelines)
- Solid understanding of statistical modeling, regression, and time series
- Experience working in cloud environments (Databricks, AWS, GCP)
- Strong software engineering skills with a focus on clean, modular, object-oriented code
- Excellent problem-solving, communication, and collaboration skills
Education
A master’s degree or bachelor’s degree in computer science or related field from a top university is required.
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