
Senior AI Algorithm Engineer @ AVENGA
1 day ago
About the Role:
We are seeking a highly skilled Senior AI Algorithm Engineer to join our team at AVENGA. As a key member of our Agile development team, you will collaborate with AI engineers, product owners, business analysts, and other developers to integrate Large Language Models (LLMs) into scalable, robust, fair, and ethical end-user applications.
Main Responsibilities:
- Design, develop, customize, optimize, and fine-tune LLM-based algorithms tailored to specific use cases such as text generation, summarization, information extraction, chatbots, AI agents, code generation, document analysis, sentiment analysis, data analysis, etc.
- Create data pipelines to curate, preprocess, and structure datasets that improve LLM-based algorithms performance and reduce biases, focusing on data quality and diversity.
- Perform thorough data exploration to understand dataset characteristics, uncover patterns, detect biases, and identify data quality issues; use statistical and visualization techniques to inform feature engineering, model selection, and optimization of LLM-based applications.
- Support prompt engineers, business analysts, and subject matter experts in crafting and optimizing prompts to guide LLM outputs, enhancing performance for specific tasks.
- Conduct rigorous experimentation, including A/B testing, to evaluate algorithm performance against benchmarks and control groups; use metrics specific to generative AI as well as pre-GenAI techniques, as required.
Requirements:
The ideal candidate will have:
- Advanced proficiency in Python, PyTorch/TensorFlow, Transformer architectures, and LangChain or similar frameworks.
- Experience in designing RAG systems, including orchestration and fine-tuning of LLMs.
- Hands-on experience with AWS services (e.g., Bedrock, SageMaker) and optionally Azure.
- Strong skills in data manipulation, dataset creation, vector databases, and NLP processing.
- Expertise in zero-shot, few-shot learning, and prompt optimization.
- Deep understanding of evaluation metrics for generative and traditional ML models.
- Experience with traditional NLP techniques, classical ML models (e.g., decision trees, SVMs, gradient boosting), and feature engineering.
- Hands-on experience deploying ML/LLM models on AWS, Azure, and cloud-based ML platforms.
- Proficiency in best practices, problem-solving, and clear communication of technical concepts.
Benefits:
As a valued member of our team, you can expect:
- A competitive salary and benefits package.
- A sport subscription.
- A training budget.
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