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Recro | Backend Python Developer
1 month ago
Title: Backend Engineer
Skills: Core Backend Python + LLM +CUDA
Education: Top Tie colleges
This role requires a strong background in machine learning, proficiency in relevant programming languages and tools, a willingness to embrace challenges, and a commitment to the best software development and testing practices. Additionally, familiarity with cloud platforms and a dedication to staying current with industry trends are essential for success in this role.
Responsibilities:
- Design and Develop Scalable Machine Learning Systems: You will be responsible for collaborating with the tech team to design and build machine learning systems that are scalable and ready for production use from the start. This involves the end-to-end development of machine learning models and pipelines. You should be able to deploy and benchmark an ML model in under 30 minutes.
- Conduct Extensive Research: You'll need to stay current with the latest machine learning technologies and research to identify the best approaches and tools for the job.
- Improve Metrics: You will develop strategies for improving metrics using real-world data. This likely involves optimizing and fine-tuning machine learning models to achieve better results.
- Infrastructure Improvements: You'll assist in enhancing and extending existing infrastructure, which may involve adding new features and optimizing performance.
Requirements:
- Python Experience: 3+ years of experience with Python.
- Generative AI Experience: You must be proficient in LLMs like Llama and Mistral and other Generative AI models like Whisper and Stable Diffusion.
- Cloud Experience: You should be familiar with cloud computing platforms, with a preference for expertise in AWS and knowledge of platforms like Google Cloud Platform (GCP) or Microsoft Azure.
- Experience with Docker and Kubernetes: You should be proficient in Docker and Kubernetes.
- Test-Driven Development: Belief in and adherence to Test-Driven Development practices is essential. This means writing tests before writing code to ensure the quality and correctness of your work.
- Deep understanding of GPU Architecture: You should have a deep knowledge of GPU Architectures like A100 A10G, and T4 chips. Experience with CUDA is a plus.
- Familiarity with LLM optimization techniques: Good enough idea of optimization techniques like Quantization, speculative decoding, continuous batching, etc.
