Senior Data Scientist

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 Data Scientist, you will own the design, prototyping, deployment, and continuous improvement of AI/ML systems that leverage LLMs, agentic AI workflows, and predictive models. You will work closely with product, engineering, and operations teams to deliver production-grade AI systems that improve the experience of millions of passengers, drivers, and users.
This role is ideal for a self-driven engineer who thrives on emerging technologies, system-level thinking, and translating research into production impact

 

What You’ll Drive Forward

• Design and build AI systems (RAG pipelines, multi-agent workflows, and predictive services).
• Develop, deploy, and optimize ML models in production.
• Collaborate with scientists, engineers, and product teams to integrate AI into core Snapp products.
• Monitor, evaluate, and continuously improve system performance (accuracy, latency, cost).
• Experiment with new AI paradigms (agentic AI, multi-modal models, RL, and LLM).
• Ensure system reliability through robust testing, observability, and version control.
• Document architecture, data flows, and processes for cross-team transparency.
• Drive technical innovation through active research and the application of new theories, techniques, and technologies.

 

What Powers Your Drive

• 3+ years of experience as a data scientist/ML engineer/AI engineer, or in a similar role, with a track record of increasing responsibility and ownership.
• Strong background in machine learning and applied AI (LLMs, deep learning, NLP, computer vision, ...).
• Deep understanding of the AI systems lifecycle: from data preprocessing and feature engineering to model training, validation, deployment, and maintenance.
• Solid engineering skills in Python
• Experience with MLOps/AI infrastructure: containers (Docker), orchestration (Kubernetes), and model serving (vLLM, Triton, or similar).
• Experience with LLM applications and agentic AI systems, including RAG, fine-tuning, and frameworks such as LangChain, LangGraph, MCP, or custom agent frameworks.
• Knowledge of evaluation frameworks (RAGAS, TrueLens, and custom rubric-based evaluations).
• Comfort with large-scale data systems (SQL, ClickHouse, Spark, Redis, etc.).
• Strong communication skills (able to explain complex systems clearly to both technical and non-technical stakeholders).
• Practical experience in experimentation, A/B testing, and statistical evaluation.
• Familiarity with multi-modal AI (vision-language models, OCR, speech).
• Ability to work independently, drive projects end-to-end, and thrive in fast-moving environments.

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.