Python Developer
Python Developer
R&D Netanya
Description
Fetcherr experts in deep learning, e-commerce, and digitization, Fetcherr disrupts traditional systems with its cutting-edge AI technology. At its core is the Large Market Model (LMM), an adaptable AI engine that forecasts demand and market trends with precision, empowering real-time decision-making. Specializing initially in the airline industry, Fetcherr aims to revolutionize industries with dynamic AI-driven solutions.
Responsibilities
• Design, build, and maintain scalable, high-performance backend services and infrastructure for Fetcherr's LLM ecosystem.
• Develop and manage APIs and microservices that facilitate the interaction between LLM models, data pipelines, and end-user applications.
• Implement and optimize data pipelines for ingesting, processing, and serving data relevant to LLM training and inference.
• Ensure the reliability, security, and efficiency of LLM deployment environments through robust infrastructure management.
• Collaborate with LLM Engineers and Data Scientists to understand their infrastructure needs and provide tailored solutions.
• Establish and maintain best practices for Python development, including coding standards, testing (unit, integration, E2E), reproducibility, and version control for infrastructure code.
• Leverage cloud platforms (e.g., GCP) to build and manage scalable infrastructure, including compute, storage, and networking resources.
• Implement monitoring, logging, and alerting systems to ensure the health and performance of LLM services and infrastructure.
• Contribute to the architectural decisions and strategic direction for Fetcherr's AI infrastructure.
• Stay abreast of industry trends and best practices in Python development, cloud computing, and MLOps.
Requirements
• 5+ years of professional experience in backend software development, with a strong emphasis on Python.
• Proven experience in building and managing production systems and scalable infrastructure.
• Strong understanding of building applications that scale and operate reliably in a cloud environment.
• Expertise in designing and implementing APIs and microservices.
• Solid experience with cloud platforms, particularly GCP (preferred), including services for compute, storage, networking, and managed databases.
• Demonstrated experience with good coding practices for testing, reproducibility, and version control (e.g., Git).
• Familiarity with containerization technologies such as Docker and orchestration platforms like Kubernetes.
• Experience with CI/CD pipelines and tools for automated testing and deployment.
• Proficiency in database technologies (SQL and NoSQL).
• Excellent problem-solving, analytical, and debugging skills.
• Strong communication and collaboration skills, with the ability to articulate technical concepts effectively.
Nice to have
• Hands-on experience with MLOps practices and tools (e.g., Kubeflow, MLflow, TensorFlow Extended).
• Experience with serving LLMs, including model optimization techniques and efficient inference.
• Knowledge of LLM frameworks and libraries (e.g., LangChain, Transformers).
• Experience with data streaming technologies (e.g., Kafka, Pub/Sub).
• Understanding of security best practices for cloud infrastructure and applications.
• Familiarity with infrastructure-as-code tools (e.g., Terraform, CloudFormation).
Контакты
