Senior Routing ML Engineer

🕒 August 19

🇵🇹 Portugal – Remote

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 58%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Bonapolia

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2018

💼 Consulting

📣 Marketing

📦 Logistics

Consulting • Marketing • Logistics

Bonapolia is a recruitment and talent-matching firm focused on connecting candidates with technology and engineering roles through a candidate-centric, client-partner approach. The company operates a global, largely remote job marketplace and offers career counseling, interview coordination, and relocation support (notably to Portugal) while building long-term relationships with clients to deliver hired talent efficiently. Bonapolia emphasizes scalable boutique recruitment services, training support for employees, and a streamlined application/connect process for job seekers.

📋 Description

• 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

🎯 Requirements

• 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 core data science libraries, including PySpark, Pandas, NumPy, Scikit-learn, PyTorch, CatBoost, XGBoost, or LightGBM • SQL proficiency • 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 • Awareness of concept drift and how to detect and manage it • Comfort working with large-scale geospatial and behavioral data, including GPS traces and H3 spatial indexing • Ability to influence teammates and cross-functional stakeholders effectively • Curious and improvement-oriented mindset with willingness to challenge existing approaches • Excellent ability to communicate complex technical findings clearly and concisely