Machine Learning
hace 5 meses
Fine-tune Large Language Models (LLMs) across multiple tasks, optimizing for efficiency and accuracy.
- Integrate knowledge graphs with LLMs to enrich AI’s understanding and interaction capabilities.
- Collaborate across teams to ensure smooth integration of AI technologies.
- Drive the evaluation and validation of AI models and algorithms through data-driven methodologies to ensure performance and reliability.
**Requirements**:
- Strong understanding of semantic caching.
- 5+ years in Machine Learning engineering or software development
- Expertise in Python programming and a solid grasp of data science tools including, but not limited to, Pandas, Scikit-learn, TensorFlow, and PyTorch.
- Experience with orchestration frameworks like LangChain, LamaIndex, and Haystack.
- Experience with prompt engineering techniques like ICL, CoT, and ReACT.
- Experience in building context augmentation layers (RAG, FLARE) and working with vector databases.
- Experience with generative models in production environments.
**Education**:
- Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Statistics, or related field.
- Additional training or certification in AI/ML is preferred.
**Nice to Have**:
- Familiarity with Front End frameworks, such as React and Angular.
- Experience/knowledge in designing, implementing, and automating MLOps infrastructure and workflows for seamless transition of ML models from development to production, ensuring scalability, reliability, and efficiency.
- Solid grasp of cloud platforms (AWS, GCP, or Azure) and their use in ML workloads.
- Solid understanding of algorithm design, data structures, and software development practices.
**Benefits**
Remote Work and Flexibility: We offer the option to work remotely, providing you with the flexibility to manage your time and achieve a healthy work-life balance. If you prefer, you can also choose to work from our office in Montevideo according to your preferences.
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