About Company
Careem is the everyday Super App for the greater Middle East, offering a host of services that simplify people’s lives. From ride-hailing and food delivery to payments, courier services, and more, Careem is on a mission to simplify and improve the lives of people and build an awesome organisation that inspires. We are a pioneer in the region’s tech ecosystem, committed to making a tangible difference in the communities we serve. Our purpose is to create an internet-era institution that fundamentally improves people’s lives in the region. We are driven by a bold vision to create the first Super App in the region, encompassing a wide array of services that cater to the evolving needs of our users. Joining Careem means becoming part of a diverse, innovative, and fast-paced environment where you can truly make an impact on millions of lives every day.
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Job Description
Are you a passionate Machine Learning Engineer eager to apply your expertise to real-world problems that impact millions of users? Careem is seeking a talented and motivated Machine Learning Engineer to join our dynamic team in Dubai. In this role, you will be instrumental in designing, developing, and deploying robust machine learning models that power various aspects of our Super App – from optimizing ride-hailing routes and predicting demand to personalizing user experiences, enhancing fraud detection systems, and improving logistics efficiency. You will work closely with data scientists, product managers, and software engineers to translate complex business challenges into scalable ML solutions. This is an exciting opportunity to contribute to a data-driven culture, leveraging cutting-edge technologies to drive innovation and deliver tangible value across our diverse product offerings. We are looking for an individual who thrives in a fast-paced environment, possesses strong problem-solving skills, and has a proven track record of bringing ML models from research to production. You will be responsible for the entire ML lifecycle, including data preprocessing, feature engineering, model training, evaluation, deployment, and monitoring. Join us and help shape the future of urban mobility and services in the region!
Key Responsibilities
- Design, develop, and deploy scalable machine learning models for various applications, including demand prediction, dynamic pricing, fraud detection, recommendation systems, and operational efficiency.
- Collaborate with data scientists to transition experimental models into production-ready systems.
- Work closely with product managers and business stakeholders to understand requirements and translate them into technical specifications and ML solutions.
- Implement and maintain robust MLOps practices, including CI/CD pipelines, model monitoring, and A/B testing frameworks.
- Perform data exploration, feature engineering, and data preprocessing to build high-quality datasets for model training.
- Optimize model performance, scalability, and reliability in a production environment.
- Stay updated with the latest advancements in machine learning and deep learning research and apply them to enhance our products.
- Contribute to the design and architecture of our machine learning platform and infrastructure.
- Mentor junior engineers and promote best practices in ML engineering.
Required Skills
- Strong proficiency in Python and relevant ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
- Solid understanding of machine learning algorithms, statistical modeling, and experimental design.
- Experience with cloud platforms (e.g., AWS, Azure, GCP) for deploying ML models and services.
- Proficiency in SQL for data querying and manipulation.
- Experience with big data technologies (e.g., Spark, Hadoop) and data warehousing concepts.
- Familiarity with MLOps principles and tools (e.g., Docker, Kubernetes, MLflow).
- Excellent problem-solving skills and ability to work independently and collaboratively.
- Strong communication skills to articulate complex technical concepts to diverse audiences.
Preferred Qualifications
- Master's or Ph.D. in Computer Science, Machine Learning, Statistics, or a related quantitative field.
- Experience with real-time ML systems and low-latency inference.
- Prior experience in the ride-hailing, e-commerce, or logistics industries.
- Familiarity with distributed systems and microservices architecture.
- Contributions to open-source projects or relevant publications.
Perks & Benefits
- Competitive salary and performance-based bonuses.
- Comprehensive health insurance and wellness programs.
- Generous paid time off and flexible work arrangements.
- Opportunities for professional development and continuous learning.
- Access to a vibrant, diverse, and inclusive work culture.
- Employee discounts on Careem services.
- State-of-the-art office facilities and modern tech stack.
- Regular social events and team-building activities.
How to Apply
Interested candidates are encouraged to apply by clicking the link below. Please ensure your resume highlights your relevant experience in machine learning engineering, including projects, tools, and outcomes. We look forward to reviewing your application and exploring how your skills can contribute to Careem’s mission.
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