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6 hours ago
As a senior machine learning engineer, you will be responsible for designing and developing innovative solutions for challenging business problems using generative AI models. The ideal candidate will have experience in building data pipelines, deploying ML/GenAI models in production, and monitoring their performance.
Key Responsibilities:- Design and Develop Generative AI Models: Using techniques like RAG, transformers, and other relevant approaches, you will develop generative AI models that meet business needs.
- Fine-Tune Pre-Trained LLMs: You will fine-tune pre-trained LLMs for specific tasks and domains to improve model performance.
- Research New Techniques: Stay up-to-date on the latest advancements in generative AI research and apply new techniques to improve model performance and capabilities.
- Apply Software Engineering Rigor: Ensure that machine learning pipelines are built with software engineering rigor and best practices.
- Evaluate and Analyze Model Performance: Evaluate and analyze ML/generative AI model performance to ensure it meets business needs.
- Bachelor's/Master's degree in Computer Science, Machine Learning, or related field.
- 5+ years of experience in generative AI or related fields.
- Strong Python programming skills.
- RAG and other generative model techniques expertise.
- Proficient in Git, Docker, and Linux server management.
- Cloud-based ecosystems experience, especially AWS ML/GenAI services.
- ML/GenAI frameworks and tools familiarity.
- Excellent communication and collaboration skills.
- Independent work ability with a team-oriented mindset.
- Methodical and meticulous work approach.
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