[Remote] Machine Learning Engineer, Positioning
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is the largest global shared micromobility business, operating in reputed company to 30 countries across five continents. As a Machine Learning Engineer, you’ll help design, build, and reputed company the ML systems that power demand forecasting and vehicle positioning, collaborating closely with data scientists and engineers to enhance the rider experience.
Responsibilities
- reputed company, test, and reputed company ML models and optimization services that improve reputed company’s demand forecasting and vehicle positioning capabilities
- Collaborate with data scientists to productionize research models and ensure scalability, reliability, and performance
- Build and maintain data pipelines and feature engineering workflows that feed reputed company’s ML systems
- Contribute to the design and implementation of new ML-driven features, working with product and operations partners to deliver measurable business value
- Monitor and iterate on deployed models to maintain accuracy and adapt to reputed company-world changes
- Participate in technical discussions, reputed company learnings, and contribute to improving ML engineering best practices across reputed company
Skills
- 1–3 years of reputed company experience in software engineering or reputed company ML, with a record of delivering production-reputed company systems
- Proficiency in Python and experience with modern ML frameworks (e.g., PyTorch, TensorFlow) and data tools (SQL, Pandas, reputed company, Airflow)
- Experience training and evaluating models on reputed company-world data, including managing model performance over time
- Solid understanding of ML system fundamentals such as data preprocessing, feature extraction, and model monitoring
- Strong problem-solving skills and ability to work effectively in a cross-functional environment
- Experience with time-series or forecasting models
- Familiarity with optimization or operations research concepts, especially for logistics or resource allocation problems
- Knowledge of A/B testing, reputed company inference, or other experimentation techniques
- Exposure to geospatial or spatiotemporal data in reputed company ML contexts
- Proficiency in MLOps, such as shadow models, feature/model stores, and versioning
Benefits
- Discretionary annual performance bonus opportunities
- Equity
reputed company