اسنپ شاپ | SnappShop

تاسیس در ۱۳۹۸ کامپیوتر، فناوری اطلاعات و اینترنت ۲۰۱ تا ۵۰۰ نفر SnappShop.ir

استخدام AI Engineer

دسته‌بندی شغلی

وب،‌ برنامه‌نویسی و نرم‌افزار
موقعیت مکانی

تهران ، تهران
نوع همکاری

تمام وقت
حداقل سابقه کار

سه تا شش سال
حقوق

توافقی

شرح موقعیت شغلی

Requirements

· Hands-on experience building and deploying Machine Learning or AI solutions in a production environment.

· Strong understanding of machine learning fundamentals, including model selection, training, evaluation, experimentation, data preparation, generalization, and error analysis.

· Strong problem-solving ability: able to take an ambiguous business or product problem, formulate it as an AI/ML problem, and determine an effective solution.

· Experience building end-to-end AI systems, from understanding the problem and data through experimentation, evaluation, deployment, and iteration.

· Familiarity with multiple approaches to AI/ML, including classical machine learning, deep learning, foundation models, embeddings, retrieval, prompting, fine-tuning, and agentic systems.

· Ability to select and combine different techniques based on the problem rather than being tied to a particular model, framework, or methodology.

· Strong familiarity with modern AI development practices, including AI-assisted development, coding agents, rapid experimentation, and automated evaluation.

· Ability to use modern AI development tools effectively to research, prototype, implement, debug, evaluate, and iterate on AI solutions while maintaining technical ownership of the resulting system.

· Strong understanding of AI system evaluation, including selecting meaningful metrics, designing experiments, analyzing failure cases, and measuring real-world impact.

· Solid Python skills sufficient to develop, understand, test, and productionize AI/ML systems.

· Proficiency in SQL and experience working with real-world data.

Duties

· AI Problem Solving: Identify, formulate, and solve complex business and product problems using AI/ML.

· AI System Design: Design end-to-end AI systems by combining models, data, prompts, retrieval, tools, agents, evaluation, and traditional software components where appropriate.

· Approach Selection: Investigate different solution strategies and determine the appropriate trade-offs between traditional ML, deep learning, foundation models, fine-tuning, RAG, prompting, and agentic approaches.

· Rapid Experimentation: Build baselines, prototype alternative approaches, run experiments, analyze failures, and rapidly iterate toward effective solutions.

· AI-Native Development: Use modern AI development tools and coding agents to accelerate research, implementation, experimentation, debugging, testing, and iteration.

· Model Development: Develop, train, fine-tune, or integrate ML models when the problem requires it.

· AI Application Development: Build practical systems around foundation models, including LLM applications, retrieval systems, structured generation, tool use, and agents.

· Evaluation: Design and maintain evaluation processes that measure AI system quality, identify failure modes, and guide further development.

· Productionization: Turn successful solutions into reliable, scalable, observable, and maintainable production systems in collaboration with engineering teams.

· Continuous Improvement: Use production feedback, experiments, and evaluation results to continuously improve AI systems.

Preferred Competencies

· Experience building LLM applications, RAG systems, agentic systems, or other foundation-model-based applications.

· Experience with model fine-tuning or parameter-efficient fine-tuning.

· Experience building automated evaluation and benchmarking systems.

· Familiarity with AI coding agents and AI-native development workflows.

· Experience with MLflow or similar experiment-tracking and MLOps tools.

· Experience in one or more applied AI domains such as search, recommendation, NLP, computer vision, forecasting, or ranking.

· Familiarity with software engineering practices such as Git, testing, debugging, and CI/CD.

· Demonstrated ability to quickly learn and apply new AI technologies, models, and development methodologies.

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معرفی شرکت

اسنپ‌شاپ با هدف تسهیل خرید آنلاین و ارائه تجربه‌ای سریع و مطمئن، فعالیت خود را در سال ۱۳۹۸ آغاز کرد. این پلتفرم با ارائه خدمات تحویل سفارش‌ها در انواع مختلف تحویل زیر سه ساعت، تحویل به‌صرفه و تجمیعی استانداردی نوین در بازار خرده‌فروشی آنلاین ایران ایجاد کرده است.
امروز اسنپ‌شاپ به‌عنوان یکی از سرویس‌های اصلی خانواده اسنپ، در مسیر توسعه پایدار و گسترش خدمات به شهرهای بیشتر قرار دارد. ما متعهدیم کیفیت خدمات خود را همگام با استانداردهای جهانی ارتقا دهیم و ارزش‌آفرینی مستمر برای مشتریان و جامعه فراهم کنیم.