GenAI (LLM) Middle Developer in Graphit

About the RoleAs an up-and-coming GenAI developer at our dynamic and rapidly expanding IT services firm, you will have the unique opportunity to immerse yourself in the cutting-edge world of Generative AI, with a particular focus on Large Language Models (LLMs). This role places you at the heart of our development process, where you will collaborate closely with Team Lead and play an integral role in the life cycle of diverse GenAI projects. The industry is extremely fast paced now, therefore, work would require fast learning and ability to take on responsibility.Responsibilities-Collaborate closely with the development team and senior engineers to gain a deep understanding of project requirements and objectives.-Develop a Large Language Model (LLM) Proof of Concepts (PoCs), taking a lead role in conceptualizing and implementing innovative ideas and solutions that push the boundaries of what's possible with GenAI.-Drive the construction and maintenance of efficient development pipelines, overseeing the process from concept to production and ensuring best practices are followed for optimal performance and scalability.-Lead junior developers in specific tasks and projects, providing mentorship and guidance to foster their growth and ensuring high-quality contributions to the development efforts.-Actively engage in problem-solving discussions, leveraging technical expertise to address and overcome business challenges faced by clients, and contributing to the strategic planning of project implementations.Must-Have Qualifications-A solid foundation in working with Large Language Models (LLMs) and their applications, backed by practical projects that showcase a deep understanding of LLM capabilities, use cases, and constraints. This experience should reflect a keen insight into the nuances of generative AI technologies.-A minimum of 3 years of professional experience in the field of Machine Learning, with a specific focus on Natural Language Processing (NLP). This should include hands-on work with a range of ML models and NLP techniques, demonstrating a track record of solving complex problems in this domain.-Proficiency in cloud-based MLOps practices, with experience in deploying large AI models into production environments. Familiarity with cloud services and platforms that support AI model scaling, management, and optimization is essential.-Experience with Docker, Flask, FastAPI, and other relevant technologies for containerizing and serving ML models in production settings. This includes understanding the best practices for developing, testing, and deploying scalable and secure AI-powered applications.- Knowledge of Vector Databases and the underlying query algorithms essential for conducting similarity searches in high-dimensional data spaces. Experience with these databases should include practical applications that leverage their unique capabilities for AI and ML projects.Nice-to-Have Qualifications-Advanced degree (Master's or Ph.D.) in Computer Science, Machine Learning, or a related field.-Knowledge of software engineering principles and practices, including version control and agilemethodologies.Show more Show less Job level Basic level Type of employment Full-time Branches IT services and IT Consulting