GenAI Lead

Job Description

Advanced degree (Master s or higher) in Computer Science, Engineering, or a closely related technical discipline. Minimum of 3 years of hands-on experience with a range of machine learning models, spanning traditional to advanced methods. Solid foundation in NLP methods, including applications like text classification, sentiment detection, and entity recognition. Proficiency with Retrieval-Augmented Generation (RAG) techniques and experience working with vector databases (e.g., Weaviate, PineCone). Extensive Python programming skills, with a proven ability to implement complex solutions. At least 1 year of practical experience in building applications based on Large Language Models (LLMs) using established third-party models (e.g., OpenAI, Anthropic). Skilled in prompt engineering, with experience crafting function calls and constructing conversational AI applications. Familiarity with advanced LLM techniques such as zero-shot and few-shot learning, as well as fine-tuning for specific use cases. Strong background in using Generative AI libraries and tools, such as Langchain and HuggingFace. Solid grasp of version control practices, including Git and collaborative development workflows. Comprehensive experience in preparing, managing, and processing extensive datasets, both structured and unstructured. Proven experience deploying, scaling, and monitoring machine learning models, particularly LLMs, in live environments. Flexible to accommodate occasional overlap with US Eastern Time for effective team collaboration. Professional proficiency in English.Desirable Additional Experience: Hands-on experience with open-source LLM frameworks, such as Llama or Mistral. Prior work involving data in regulated sectors, such as healthcare, banking. Technical Skills and Capabilities: Skilled in RESTful API design (Python-FastAPI) and development, ensuring secure and scalable interfaces. Proficient in JavaScript for both front-end and back-end, with a strong command of associated frameworks. Knowledgeable in architecting scalable solutions using microservices. Experience with the generative AI landscape, specifically around RAG, vector embeddings, LLMs, and open-source AI toolkits. Familiarity with cloud-based infrastructure (AWS, Azure, GCP) and their data services. Competent in database design and optimization across SQL and NoSQL technologies. Practical experience with data streaming platforms, such as Kafka, Azure Event Hub, or AWS Kinesis. Agile development experience, using tools like Git, Jenkins, and Azure DevOps. Skilled in creating and managing CI/CD pipelines for seamless testing and deployment. Excellent team collaboration and communication skills, with an aptitude for working across technical and non-technical roles. 3 Must Skills Gen AI 4/5 AWS 4/5 SQL 4/5