Backend Development Specialist

2 days ago

Lahore, Punjab, Pakistan beBeeBackend Full time 900,000 - 1,200,000
Backend Development Specialist

We are looking for a highly skilled specialist with expertise in backend development, DevOps practices, and AI/ML technologies.

The ideal candidate will have experience in building robust, scalable applications, integrating advanced NLP and generative AI solutions, and implementing efficient web scraping systems. You will play a critical role in designing, deploying, and maintaining applications, ensuring high performance and reliability.

Key Responsibilities:
  • Develop, maintain, and optimize backend systems using Python and its frameworks (e.g., Django, Flask, FastAPI).
  • Build and deploy scalable APIs and microservices to support AI/ML-powered applications.
  • Design and implement NLP and generative AI models for solving real-world problems.
  • Develop efficient web scraping tools and pipelines for data extraction and processing.
  • Implement DevOps practices, including CI/CD pipelines, containerization (Docker), and orchestration (Kubernetes).
  • Ensure system reliability and scalability by working with cloud platforms (AWS, Azure, or GCP).
Requirements:
  • 4+ years of experience in Python development with a strong focus on backend systems.
  • Proven expertise in DevOps tools and practices (CI/CD, Docker, Kubernetes, Infrastructure as Code).
  • Solid understanding of AI/ML frameworks like TensorFlow, PyTorch, Hugging Face, or similar.
  • Experience with NLP techniques, libraries (spaCy, NLTK), and generative AI models (e.g., GPT, T5).
  • Proficiency in web scraping frameworks and tools (e.g., Scrapy, Beautiful Soup, Selenium).
  • Hands-on experience with RESTful APIs, GraphQL, and microservices architecture.
  • Familiarity with relational (PostgreSQL, MySQL) and NoSQL databases (MongoDB, Cassandra).
  • Knowledge of cloud services and infrastructure (AWS, Azure, GCP).
PREFERRED SKILLS:
  • Tangible demonstrable experience with Pytorch and TensorFlow is a must.
  • Familiarity with big data tools (e.g., Apache Spark, Hadoop).
  • Experience with MLOps workflows for AI model deployment and lifecycle management.
  • Understanding of large-scale data processing pipelines and data lakes.

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