About the role
As a Applied AI Engineer, you will be instrumental in designing, building, and scaling our enterprise-level systems. Your expertise will be crucial in developing cutting-edge solutions that leverage the latest in AI and machine learning.
What you'll do
- Lead the design and development of robust, scalable, and cloud-native software architectures.
- Implement complex features and functionalities using Python and modern development frameworks and best practices.
- Develop sophisticated Agentic Workflows leveraging leading industry frameworks.
- Apply your deep understanding of Deep Learning concepts (e.g., Stochastic Gradient Descent, Backpropagation) and Machine Learning fundamentals (e.g., clustering, classification, regression, tree-based algorithms) to solve real-world problems.
- Design scalable user interface using latest JavaScript frameworks.
- Leverage your knowledge of Natural Language Processing (NLP) fundamentals (e.g., BERT, Bag-of-Words, Part-of-speech tagging, entity recognition, sentiment analysis) to extract insights from diverse datasets.
- Drive the implementation of Generative AI solutions, demonstrating expertise in Transformer models, embeddings, tokenization, prompt engineering, prompt tuning, and a thorough understanding of Retrieval Augmented Generation (RAG) pipelines.
- Strategize and implement various data chunking strategies and work with diverse vector database technologies and their underlying similarity search techniques.
- Optimize RAG pipelines and ensure system observability and monitoring using MLOps practices and relevant tools.
- Utilize and evaluate solutions with various AI model evaluation methodologies and tools.
- Navigate and prioritize multiple complex requirements in a fast-moving environment.
- Contribute to a positive and collaborative team culture, driving innovation and continuous improvement.
What we're looking for
- Junior & Mid-level experience as a hands-on software engineer, with a proven track record of building and deploying enterprise-level, cloud-native, and scalable systems.
- Advanced proficiency in Python and its associated development ecosystem.
- Demonstrable experience developing Agentic Workflows using industry-leading frameworks.
- Solid understanding of Deep Learning and Machine Learning fundamentals.
- Strong grasp of Natural Language Processing (NLP) fundamentals.
- In-depth knowledge of Generative AI fundamentals, particularly RAG pipelines and related technologies (e.g., transformer models, embeddings, tokenization, prompt engineering/tuning, chunking strategies, vector databases, similarity searches).
- Experience with RAG pipeline optimization techniques and familiar with MLOps, observability, and monitoring tools.
- Proficiency in using evaluation metrics for AI models.
- Exceptional problem-solving skills and the ability to adapt to evolving project requirements.