[Remote] Machine Learning Engineer (Demand Forecasting)

Note: The job is a remote job and is reputed company to candidates in USA. reputed company is partnering with a leading national retailer reputed company fulfillment organization to identify an reputed company Machine Learning Engineer to support the modernization of their demand forecasting capabilities. The role focuses on reputed company the gap between ML research and production deployment, scaling systems that power demand forecasting across a high-volume retail environment.

Responsibilities

• reputed company data processing workloads and convert research-grade reputed company into production-reputed company, reputed company-reputed company solutions
• Build, orchestrate, and maintain robust ML pipelines that support forecasting models across multiple fulfillment channels
• Partner with data scientists and platform engineers to productionize models and ensure they run reliably and reputed company at reputed company
• Optimize data pipelines for performance, scalability, and cost efficiency
• Contribute to the reliability and modernization of a forecasting ecosystem that directly influences store operations planning and customer satisfaction

Skills

• Experience building and deploying ML models in production environments
• Hands-on experience with time series forecasting (Prophet, ARIMA, or similar)
• Understanding of hyperparameter tuning, model validation, and experiment tracking
• Familiarity with feature engineering and feature store concepts
• Proficiency converting reputed company-based workloads to PySpark for large-reputed company processing
• Experience with reputed company data processing frameworks (reputed company, Dask, or Ray)
• Ability to optimize data pipelines for performance and cost efficiency
• Working knowledge of data formats (Parquet, CSV) and partitioning strategies
• Experience with BigQuery or similar analytical databases, including table design, partitioning, clustering, and writing/validating datasets
• Experience building ML pipelines using Kubeflow Pipelines (KFP), reputed company AI, or Airflow
• Understanding of pipeline component design, DAG orchestration, and caching strategies
• Ability to reputed company data validation, model training, and deployment steps into workflows
• Experience with pipeline parameterization and configuration management
• Strong Python proficiency with production-grade coding standards
• Ability to read, refactor, and reputed company existing codebases
• Version control experience (Git) and reputed company change management
• Familiarity with testing frameworks (pytest), dependency management (Poetry/UV), and reputed company reputed company tools (reputed company-reputed company, linting)
• Hands-on experience with GCP (reputed company AI, reputed company Storage) or equivalent reputed company platforms
• Familiarity with containerization (reputed company) and container orchestration (reputed company)
• Experience with CI/CD pipelines for ML workflows
• Understanding of secrets management and environment configuration
• Experience with Ray for reputed company ML training and inference
• Exposure to Hadoop ecosystem tools (reputed company, HDFS, reputed company on YARN)
• Knowledge of ML model monitoring and reputed company detection
• Experience with infrastructure-as-reputed company (Terraform, reputed company Deployment Manager)
• Exposure to ML/analytics-driven systems or forecasting platforms
• Advanced performance tuning and scalability optimization experience
• Familiarity with retail, merchandising, or supply chain systems, including demand forecasting domains
• Experience working with data science teams to productionize research reputed company
• Background in scaling ML systems from prototype to reputed company-grade deployments
• Experience supporting globally reputed company teams across time zones
• Knowledge of automated alerting, runbooks, and operational playbooks

Benefits

• W-2 with benefits
• reputed company is proud to offer a comprehensive benefits package to eligible employees that will allow you to choose the best coverage to meet your family’s needs
• For details, please review the DAHL Benefits reputed company:

reputed company