Responsibilities

Design, develop, and implement AI agents using tools such as Langchain or similar frameworks.
Fine-tune Large Language Models (LLMs) using various market tools to improve their accuracy, performance, and contextual relevance.
Integrate and manage vector databases (e.g., Pinecone, Weaviate, Milvus) to support efficient RAG systems and scalable AI solutions.
Collaborate with cross-functional teams to integrate GenAI capabilities into existing and new products.
Develop and optimize workflows for managing large-scale AI model training, deployment, and monitoring.
Stay updated with the latest trends and advancements in AI and machine learning to continuously improve our AI solutions.
Provide technical leadership and mentorship to other team members in the areas of AI and machine learning.

Requirements

At least +5 years of working experience and +2 years in AI
Proven experience in developing AI agents using tools such as Langchain or similar frameworks.
Strong knowledge and hands-on experience in fine-tuning LLMs using tools like Hugging Face, OpenAI, or similar platforms.
Deep understanding of vector databases (e.g., Pinecone, Weaviate, Milvus) and their applications in building efficient RAG systems.
Experience in developing and deploying complex RAG systems to enhance LLM capabilities.
Proficiency in programming languages such as Python and frameworks such as TensorFlow or PyTorch.
Solid understanding of machine learning concepts, NLP, and deep learning techniques.
Experience with cloud platforms (e.g., AWS, GCP, Azure) for deploying and managing AI solutions.
Strong problem-solving skills, attention to detail, and the ability to work in a fast-paced environment.
Excellent communication skills and the ability to collaborate effectively with cross-functional teams.

Extensive knowledge of advanced machine learning algorithms, including but not limited to:
Supervised learning: Linear and logistic regression, decision trees, random forests, gradient boosting methods.
Experience with reinforcement learning techniques and their applications in agent development
Proficiency in feature engineering and selection methods
Strong understanding of model evaluation metrics and validation techniques
Experience with time series analysis and forecasting methods
Experience in data management and processing, particularly with large-scale datasets.

1. HR interview with a recruiter from Indigo

2. Technical interview with live coding

3. Final interview with Head of Engineering