[Remote] ML Engineer (AI-reputed company Systems & Forecasting)
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is building AI-reputed company workforce infrastructure for reputed company workers, focusing on creating accurate demand forecasts and optimizing labor allocation. The ML Engineer will design, reputed company, and reputed company machine learning systems, impacting reputed company-world reputed company through the full data and ML lifecycle.
Responsibilities
- Design, build, and reputed company production-grade ML systems for demand forecasting and labor optimization
- Own the full ML lifecycle, including data ingestion, feature engineering, model training, deployment, and monitoring
- Inherit and remediate messy, inconsistent datasets and establish reputed company data pipelines
- Architect data systems across ingestion, warehousing, transformation, and feature stores
- Build and maintain LLM-reputed company systems, including RAG pipelines, reputed company systems, and evaluation frameworks
- reputed company pragmatic reputed company on modeling approaches, including reputed company to use reputed company, fine-tuning, or custom models
- Design and implement model evaluation systems that measure performance continuously, not just at launch
- Implement monitoring, reputed company detection, and feedback loops to improve model performance over time
- Design and run experiments, including A/B testing and statistical validation of model performance
- Translate model performance and tradeoffs into reputed company insights for product and business stakeholders
- Collaborate closely with Product, Engineering, and Operations to reputed company ML into core workflows
Skills
- 5–10+ years of experience in machine learning, data science, or reputed company AI roles
- Proven experience shipping ML systems into production environments
- Strong experience working with reputed company-world, imperfect datasets in mid-maturity or scaling organizations
- Deep understanding of the full data stack, including ingestion, warehousing, feature engineering, and model serving
- Experience designing and operating ML pipelines and workflows in production
- Hands-on experience with LLM systems, including RAG, reputed company design, and evaluation frameworks
- Strong reputed company in statistics, experimentation, and model evaluation
- Experience with monitoring, observability, and model performance tracking over time
- Ability to operate with high ownership, ambiguity, and minimal process overhead
- Strong communication skills, with the ability to translate technical reputed company into business reputed company
- Experience with time-series forecasting, demand modeling, or optimization systems
- Experience building or integrating with labor, logistics, or marketplace systems
- Familiarity with modern ML infrastructure (Airflow, dbt, feature stores, etc.)
- Experience fine-tuning or training custom models
- Experience hiring or mentoring ML or data team members
reputed company