Senior ML Engineer- (Python)

Snoonu is Qatar’s homegrown Super App, reinventing daily life with blazing-fast delivery, shopping, and more – all in one place. Powered by tech, driven by a global team, and obsessed with making life easier.

What You’ll Get Your Hands On

• Own end-to-end projects, aligning with stakeholders to translate business needs into solutions.

• Architect, develop, and maintain backend microservices and APIs in Python, ensuring scalability, resilience, and low-latency performance.

• Partner with data scientists, product managers, and engineers to design and deliver scalable, production-grade solutions aligned with business goals.

• Set technical standards through in-depth code reviews, enforcing best practices, and driving engineering excellence.

• Monitor and optimize application performance, troubleshoot issues, and implement necessary fixes.

• Own production deployments, ensuring smooth rollouts, monitoring, and rollback strategies.

• Participate in technical interviews to evaluate candidates' technical skills.

• Stay up-to-date with the latest industry trends and advancements in Python backend development, ensuring our capabilities remain competitive and cutting-edge.

• Provide technical leadership, mentor engineers across levels, and foster a high-performance, collaborative environment.
  
  

The Magic You Bring

• MSc in Computer Science, Engineering, or a related field; advanced education in Data Science/AI is a plus.

• 5+ years of experience as a Python Backend Developer with strong expertise on building production-grade ML systems.

• Proficiency in designing and implementing RESTful APIs and API authentication mechanisms.

• Expertise in writing and maintaining unit tests to ensure code quality and reliability.

• Expertise in optimizing large-scale, distributed backend systems and resolving complex performance bottlenecks.

• Deep expertise in relational databases (e.g. PostgreSQL, MySQL), NoSQL databases, and streaming/pub-sub systems.

• Experience with cloud platforms (e.g. AWS, Azure, Google Cloud) and containerization (e.g. Docker, Kubernetes).

• Proven experience designing and scaling event-driven architectures.

• Familiarity with CI/CD pipelines and version control systems.

• Excellent problem-solving skills and ability to work independently as well as in a team-oriented, collaborative environment.

• Strong communication and collaboration skills, with the ability to work effectively within a diverse, cross-functional team.
  
  

Bonus Points If You Have

• Hands-on experience integrating DL/ML models into production systems (TensorFlow, PyTorch, scikit-learn) and building APIs/services around them.

• Formal Education in Data Science / Solid understanding of machine learning algorithms, statistical methods, and data mining techniques.