
Senior Data Scientist
- On-site
- Tehran, Tehrān, Iran, Islamic Republic of
- Tech
Job description
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.).
Ability to work independently, drive projects end-to-end, and thrive in fast-moving environments.
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).
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.
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