Responsibilities
- Design and implement RAG-based solutions to enhance LLM capabilities with external knowledge sources
- Develop and optimize LLM fine-tuning strategies for specific use cases and domain adaptation
- Create robust evaluation frameworks for measuring and improving model performance
- Build and maintain agentic workflows for autonomous AI systems
- Collaborate with cross-functional teams to identify opportunities and implement AI solutions
Basic qualifications
- Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field.
Preferred qualifications
- Experience with popular LLM frameworks (Langchain, LlamaIndex, Transformers)
- Knowledge of prompt engineering and chain-of-thought techniques
- Experience with containerization and microservices architecture
- Background in Reinforcement Learning
- Contributions to open-source AI projects
- Experience with ML ops and model deployment pipelines
- Strong problem-solving and analytical skills
- Excellent communication and collaboration abilities
- Experience with agile development methodologies
- Ability to balance multiple projects and priorities
- Strong focus on code quality and best practices
- Understanding of AI ethics and responsible AI development
Tags & focus areas
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