[Remote] Machine Learning Engineer, Positioning

Remote Full-time
Note: The job is a remote job and is open to candidates in USA. Lime is the largest global shared micromobility business, operating in close to 30 countries across five continents. As a Machine Learning Engineer, you’ll help design, build, and scale the ML systems that power demand forecasting and vehicle positioning, collaborating closely with data scientists and engineers to enhance the rider experience. Responsibilities Develop, test, and deploy ML models and optimization services that improve Lime’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 Lime’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 real-world changes Participate in technical discussions, share learnings, and contribute to improving ML engineering best practices across the team Skills 1–3 years of professional experience in software engineering or applied ML, with a record of delivering production-quality systems Proficiency in Python and experience with modern ML frameworks (e.g., PyTorch, TensorFlow) and data tools (SQL, Pandas, Spark, Airflow) Experience training and evaluating models on real-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, causal inference, or other experimentation techniques Exposure to geospatial or spatiotemporal data in applied ML contexts Proficiency in MLOps, such as shadow models, feature/model stores, and versioning Benefits Discretionary annual performance bonus opportunities Equity Company Overview Lime is an electric vehicle company that provides e-bike and e-scooter rental services. It was founded in 2017, and is headquartered in San Francisco, California, USA, with a workforce of 501-1000 employees. Its website is
Apply Now

Similar Opportunities

[Remote] Software Engineer Intern (TikTok-Search) - 2026 Summer(BS/MS)

Remote Full-time

Digital Media Senior Analyst, Retail Media

Remote Full-time

2026 Summer Intern - Autonomous Vehicle Systems and Integration (Bachelors Degree)

Remote Full-time

Government Contracts Associate

Remote Full-time

Travel Mammography Tech - Weekly Pay

Remote Full-time

Account Manager - TikTok Shop (Supplements)

Remote Full-time

Software Engineer - Intern

Remote Full-time

[Remote] Loan Servicing Setup Specialist

Remote Full-time

Americas Delivery Center Finance and Accounting Analyst

Remote Full-time

Travel CT Tech - Weekly Pay

Remote Full-time

Experienced Live Chat Agent – Launch a Thriving Career in Customer Support from Home, $25-$35/hr

Remote Full-time

New Worker Friendly Online Work Entry Level Chat Support Role Available

Remote Full-time

[Remote] Remote BCBA - Spanish Speaking (United States)

Remote Full-time

**Experienced Remote Data Entry Specialist – Precision and Efficiency Expert for blithequark's Staffing and Recruiting Sector**

Remote Full-time

Experienced Remote Data Entry Administrator – Career Development Opportunities with Flexible Scheduling at arenaflex

Remote Full-time

Support Lead Part Time – Amazon Store

Remote Full-time

Electronic Warfare Software Developer

Remote Full-time

QA Test Automation Engineer -Remote

Remote Full-time

**Experienced Remote Data Entry Specialist – Maintaining Operational Efficiency at arenaflex**

Remote Full-time

Sales Associate (Optometry Focus)

Remote Full-time
← Back to Home