Senior Machine Learning Engineer

Our Journey So Far
At Snapp, we’re redefining how cities move. Our ride-hailing and mobility platform connects millions of riders and drivers every day, delivering safe, reliable, and efficient transport solutions. Powered by real-time data and robust infrastructure, we make urban travel faster, simpler, and more sustainable. We operate with the mindset of a global tech leader and the agility of a startup, building services that scale across markets while staying responsive to local needs.


Your Impact
As a Senior Machine Learning Engineer, you will own the design and deployment of scalable machine learning systems to improve travel time predictions, routing, and traffic-aware systems that power our core platform. You will work hands-on to tackle complex challenges in areas where data and outcomes may be uncertain, ensuring our systems are both reliable and innovative. Your expertise will set strong engineering standards, and you will have the opportunity to mentor junior engineers while contributing fresh ideas to continuously improve our technology and impact.
 

What You’ll Drive Forward

• Design, build, and deploy machine learning models and pipelines in production.
• Solve open-ended, uncertain, and challenging problems by combining scientific and engineering approaches.
• Apply software engineering best practices (e.g., CI/CD, testing, code reviews, versioning, monitoring).
• Collaborate with product, data, and engineering teams to turn business needs into ML solutions.
• Constantly explore novel approaches and contribute innovative ideas for improving our ML systems.
• Mentor junior engineers and help them grow their skills.
• Ensure scalability, reliability, and performance of ML solutions in production environments.

What Powers Your Drive

• 5+ years of professional experience in ML engineering, data science, or related fields.
• Proven ability to work with complex, uncertain problem spaces and deliver impactful solutions.
• Strong hands-on experience with ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn) and modern data pipelines.
• Solid knowledge of software engineering principles (e.g., distributed systems, APIs, code optimization, testing).
• Proficiency in Python.
• Experience with containerized environments (Docker, Kubernetes).
• Excellent problem-solving, communication, and collaboration skills.

Nice to Have:
● Previous experience in a technical leadership role or leading a small team.
● Domain experience with geospatial, map, or traffic data.
● Experience with MLOps tools such as MLFlow, Airflow, and DCV.
● Familiarity with Golang.

Ready to Get on Board?
Help us shape the future of ride-hailing and urban mobility. Submit your CV and let’s build smarter cities together.