Senior Routing ML Engineer

Описание вакансии

#vacancy#вакансия#job#RoutingMLEngineerSenior Routing ML Engineer

Language Proficiency: Upper-Intermediate

Candidate Location: Poland, Kazakhstan, EU, Georgia, Armenia, Serbia

Working Time Zone: CET

Planned Work Duration: July – December

Customer Description:

The customer is a global mobility and urban services platform providing transportation and other on-demand services through a digital marketplace.

Project Description:

The work spans deep learning model development, large-scale geospatial data pipelines, and low-latency production serving. The candidate will measure the impact through offline evaluation metrics and the results of online experiments

Project Phase:

ongoing

Soft Skills:

• Ability to influence teammates and cross-functional stakeholders effectively.

• Curious and improvement-oriented mindset with a willingness to challenge existing approaches.

• Excellent ability to communicate complex technical findings in a clear and concise manner.

Hard Skills / Must Have:

• 5+ years of machine learning engineering experience building and deploying deep learning models in production.

• Experience building regression, forecasting, or other supervised machine learning systems for production prediction tasks.

• Expert-level proficiency in Python and its core data science libraries (e.g., PySpark, Pandas, NumPy, Scikit-learn, PyTorch; gradient-boosting libraries such as CatBoost/XGBoost/LightGBM).

• SQL.

• Ability to design an ML system from scratch, including data analysis and processing.

• Experience translating business goals into ML problems with appropriate metrics and non-functional requirements.

• Experience designing and evaluating ML experiments.

• Experience with MLOps tools.

• Experience working with large-scale geospatial and behavioral datasets.

• Experience deploying models to production on ML serving infrastructure and optimizing for latency, and awareness of concept drift and how to detect and manage it.

• Comfort working with large-scale geospatial and behavioral data (e.g., GPS traces, H3 spatial indexing)

Hard Skills / Nice to Have (Optional):

• Academic background in Computer Science, Mathematics, or a related discipline.

• Experience with travel time prediction, traffic estimation, or routing quality.

• Experience with open-source routing engines.

• Knowledge of map matching, speed profiles, road graph tiles, and historical traffic.

• Experience with mapping, location, or geospatial products.

• Experience building products for developing markets.

• Experience with cloud data and machine learning platforms.

Responsibilities and Tasks:

• Design and build machine learning models to improve routing and travel time prediction.

• Develop traffic estimation models using large-scale GPS data.

• Implement map-matching solutions for noisy GPS data.

• Improve travel time calculation, smoothing, and rerouting logic.

• Translate routing objectives into machine learning objectives and evaluation metrics.

• Lead offline and online model evaluation activities.

• Collaborate with backend engineers to deploy low-latency production models.

• Partner with product and operations teams to define new features and requirements.

• Own the production ML lifecycle, including serving, monitoring, drift detection, and retraining pipelines.

Technology Stack: Python, SQL, PySpark, Pandas, NumPy, Scikit-learn, PyTorch, XGBoost, LightGBM, CatBoost, MLOps, ML Lifecycle Management, Production ML Systems, ML Infrastructure, Geospatial Analytics, GPS Data, H3 Spatial Indexing

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