Senior Machine Learning Engineer at invygo

Cairo, Cairo, Egypt -

Full Time

Start Date

Immediate

Expiry Date

21 Feb, 26

Salary

0.0

Posted On

23 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Data Science, Python, AWS, ETL, Risk Modeling, Churn Prediction, Dynamic Pricing, Data Engineering, MLOps, MongoDB, Redshift, Docker, FastAPI, Time-Series Forecasting, Customer Lifecycle Prediction

Industry

technology;Information and Internet

Description

About invygo invygo is transforming car ownership in the Middle East through its flexible and digital-first car subscription platform. Our goal is to make car access simple, affordable, and commitment-free. Backed by top-tier investors and operating across the region, invygo is on a mission to lead the mobility revolution in MENA. About the role At invygo, we are redefining the way people access and lease cars. We’re looking for a Senior Machine Learning Engineer to join our data science and engineering team, driving innovation in how we price, plan, and manage our car rental operations. You’ll work on end-to-end development of ML models powering dynamic pricing, churn prediction, risk assessment, and demand forecasting. This role bridges data science, engineering, and business — deploying scalable machine learning solutions that directly impact revenue, utilization, and customer satisfaction. You’ll be working in a cloud-first environment, leveraging AWS to build robust data pipelines and production-grade ML systems. What you will be doing Model Development & Deployment Dynamic Pricing - optimize subscription rates in real time based on supply, demand, and external factors. Churn Prediction - identify and retain at-risk customers. Risk Scoring - detect potential defaults. Recommendation system - personalize customer experience. Data Engineering & MLOps Design and maintain scalable ETL workflows using AWS Glue and Redshift. Automate model retraining, evaluation, and deployment pipelines to ensure continuous performance and scalability. Collaboration & Impact Partner with data analysts, and business teams to translate insights into operational models. Monitor production models for performance drift, accuracy, and stability. Contribute to improving internal ML infrastructure, data quality, and documentation. What You Bring to the Table: 4+ years of experience in DS/ML Strong background in Machine Learning (supervised and unsupervised methods, time-series forecasting, risk modeling, etc.) Strong product sense — able to translate business goals and constraints into effective ML system designs, including model targets, performance metrics, and experiment strategies Proficiency in Python and key ML/data libraries (e.g., numpy, pandas, scikit-learn, lgbm, pytorch/tensorFlow) Hands-on experience with AWS services (Glue, Lambda, S3, Redshift, SageMaker). Experience working with MongoDB and large-scale analytical databases (Redshift or similar). Knowledge of deploying ML models into production environments and maintaining model lifecycle (Docker, FastAPI) Background in pricing optimization, risk modeling, or customer lifecycle prediction in the mobility/marketplace/fintech or similar domains Interest in staying up to date with current best practices in your areas of expertise Working proficiency and communication skills in verbal and written English Why You’ll Love Working with Us At invygo, you’ll have the autonomy, resources, and support to make big things happen. You’ll learn fast, grow faster, and see your impact every single day. Here’s what we offer: 🚙 Competitive Salary 🚙 Employee Stock Options (because we want you to share in our success) 🚙 Team and Individual Performance Bonuses 🚙 Flexibility: Work from home or abroad 🚙 Discounts on invygo’s car subscription (yes, your rides just got cooler) 🚙 Team Engagement Days filled with collaboration and fun 🚗 Ready to Drive Change? If you’re someone who thrives on challenges, enjoys working in a dynamic environment, and wants to make an impact, we’d love to meet you.

Responsibilities

The Senior Machine Learning Engineer will develop and deploy machine learning models for dynamic pricing, churn prediction, risk scoring, and recommendation systems. This role involves designing scalable ETL workflows and collaborating with data analysts and business teams to translate insights into operational models.