Senior Machine Learning Engineer
2 days ago
About Recro:
We are a cutting-edge tech company that leverages machine learning and AI to drive innovation. Our team of experts is passionate about pushing the boundaries of what's possible with technology.
Salary Range:$120,000 - $180,000 per annum
Job Description:
We are seeking an experienced Backend Python Developer to join our team as a Senior Machine Learning Engineer. The ideal candidate will have a strong background in machine learning, proficiency in relevant programming languages, and a willingness to embrace challenges.
Responsibilities:
- Design and Develop Scalable Machine Learning Systems: Collaborate with the tech team to design and build machine learning systems that are scalable and ready for production use from the start. End-to-end development of machine learning models and pipelines.
- Conduct Extensive Research: Stay current with the latest machine learning technologies and research to identify the best approaches and tools for the job.
- Improve Metrics: Develop strategies for improving metrics using real-world data. Optimizing and fine-tuning machine learning models to achieve better results.
- Infrastructure Improvements: Assist in enhancing and extending existing infrastructure, adding new features and optimizing performance.
Requirements:
- Python Experience: 3+ years of experience with Python.
- Generative AI Experience: Proficient in LLMs like Llama and Mistral, and other Generative AI models like Whisper and Stable Diffusion.
- Cloud Experience: Familiar with cloud computing platforms, with a preference for AWS and knowledge of GCP or Azure.
- Experience with Docker and Kubernetes: Proficient in Docker and Kubernetes.
- Test-Driven Development: Adhere to Test-Driven Development practices, writing tests before code to ensure quality and correctness.
- Deep Understanding of GPU Architecture: Knowledge of GPU Architectures like A100 A10G and T4 chips, with CUDA experience a plus.
- Familiarity with LLM Optimization Techniques: Good understanding of optimization techniques like Quantization, speculative decoding, continuous batching, etc.
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