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کد آگهی: KP1458137839
استخدام Python Developer
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آلومینیوم دیتاست | Aluminium Dataset
در تهران
اطلاعات شغل:
نوع همکاری: تماموقت
مهارتهای مورد نیاز:
Python
Django
Git
RestFul API
OOP
پرداختها: توافقی
متن کامل آگهی:
The Mid-Level Python Developer at ALDataset plays a key role in building robust, scalable, and high-performance backend systems that power our AI platforms, data pipelines, machine learning workflows, and intelligent applications. You will design, implement, and maintain clean, efficient Python code while collaborating closely with Data Scientists, ML Engineers, Product Managers, DevOps, and frontend teams to deliver production-grade solutions in a fast-moving AI environment. This position bridges junior execution and senior architecture, taking ownership of features, modules, and integrations while contributing to best practices, code quality, and system reliability.
You will work on mission-critical components such as data ingestion pipelines, model serving APIs, real-time inference endpoints, ETL processes, and internal tooling—leveraging ALDataset’s proprietary datasets, cloud infrastructure, and modern Python ecosystem to accelerate AI innovation and deliver measurable business impact.
Key Responsibilities:
- Core Development & Implementation — Write clean, maintainable, and performant Python code following PEP 8/PEP 257 standards; develop backend services, RESTful/GraphQL APIs, and microservices using modern frameworks (FastAPI, Flask, Django).
- API & Service Development — Design and implement high-throughput, low-latency APIs for model inference, data querying, and internal tooling; ensure proper versioning, authentication (JWT/OAuth), rate limiting, and error handling.
- Testing & Quality Assurance — Write comprehensive unit, integration, and end-to-end tests (pytest, unittest); achieve high test coverage; implement CI/CD pipelines and participate in code reviews to maintain code quality.
- Performance & Scalability — Profile and optimize Python applications for speed and memory efficiency; apply asynchronous programming (asyncio), multiprocessing, and caching strategies (Redis, Memcached) where appropriate.
- Cloud & Infrastructure Collaboration — Deploy and manage Python applications on cloud platforms (AWS, GCP, Azure); work with Docker, Kubernetes, Terraform, and serverless architectures (Lambda, Cloud Functions).
- Security & Compliance — Follow secure coding practices; handle sensitive data responsibly (encryption, anonymization); ensure compliance with data privacy standards (GDPR, CCPA) in AI systems.
Qualifications & Requirements:
- Professional Experience — 2–6 years of hands-on Python development experience in production environments; proven track record delivering backend systems, APIs, or data-intensive applications.
- Core Python Mastery — Deep proficiency in modern Python (3.9+); strong understanding of advanced features (decorators, generators, context managers, metaclasses, async/await, typing).
- Frameworks & Tools — Solid experience with at least one major web framework (FastAPI preferred, Flask/Django acceptable); familiarity with SQLAlchemy, Pydantic, Alembic for databases/migrations.
- Databases & Data Handling — Practical knowledge of relational (PostgreSQL, MySQL) and NoSQL (MongoDB, Redis) databases; experience with data manipulation libraries (Pandas, NumPy, Polars).
- Testing & CI/CD — Proficient in writing tests (pytest); experience with Git, GitHub Actions/Jenkins/GitLab CI, Docker for containerization.
- Cloud & DevOps Basics — Hands-on experience deploying Python apps to cloud (AWS/GCP/Azure); understanding of containers, orchestration, and infrastructure-as-code concepts.
- Soft Skills — Strong problem-solving and debugging abilities; excellent communication for technical discussions and documentation; ability to work independently and collaboratively in agile teams.
- Portfolio / Evidence — GitHub repositories, personal projects, or professional work samples demonstrating clean architecture, testing, and real-world impact preferred.
Preferred Qualifications:
- Experience in AI/ML-adjacent development (model serving, feature engineering, MLOps tools like MLflow, Kubeflow).
- Familiarity with message queues (RabbitMQ, Kafka), streaming (Spark Streaming, Flink), or observability stacks.
- Exposure to microservices architecture, domain-driven design, or hexagonal/clean architecture patterns.
- Knowledge of frontend integration (REST/GraphQL consumption in React/Vue/Svelte).
- Contributions to open-source Python projects or internal tooling/libraries.
- Understanding of performance optimization in data-heavy or real-time AI systems.
Join ALDataset to build the Python backbone of tomorrow’s AI platforms. If you love writing elegant, efficient code that powers intelligent systems and want to grow in a high-impact, collaborative environment—apply now!
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