Software Engineer (Language Modeling), BS+12 yrs

Description: We are seeking a highly skilled and motivated Sr. LLM Engineer to join our team in driving the advancement of our Language Model infrastructure. As a key member of our AI/ML team, you will be responsible for the training, hosting, and optimization of Large Language Model (LLM) instances within our compute environment. The ideal candidate should possess a strong passion for pushing the boundaries of language technology, a deep understanding of LLM architectures, and the grit to tackle complex challenges head-on. This role requires a self-reliant individual with a drive to identify and fix inefficiencies, constantly striving to improve the codebase and optimize model performance. If you thrive in a fast-paced environment and have an unwavering commitment to delivering cutting-edge language solutions, this position is for you. Responsibilities: • Design, develop, and maintain the infrastructure for training, hosting, and serving LLM instances. • Optimize model training pipelines to achieve high performance and resource efficiency. • Implement and integrate state-of-the-art LLM architectures and techniques. • Collaborate with cross-functional teams to understand business requirements and deliver impactful language solutions. • Monitor and analyze model performance metrics, identifying areas for improvement and implementing optimizations. • Develop and maintain documentation, best practices, and coding standards for LLM development and deployment. • Stay up-to-date with the latest advancements in LLM research and industry trends, and incorporate them into our projects. • Mentor and guide junior engineers, fostering a culture of continuous learning and knowledge sharing. Skills Requirements: • 12+ years of experience in software engineering, with a focus on machine learning or natural language processing. • Degree in Computer Science, Artificial Intelligence, or a related field. • Strong expertise in deep learning frameworks such as TensorFlow, PyTorch, or MXNet. • Proficiency in programming languages such as Python, C++, or Java. • Solid understanding of LLM architectures, training techniques, and evaluation methodologies. • Familiarity with cloud platforms (e.g., AWS, GCP) and their machine learning services. • Knowledge of software engineering best practices, including version control, testing, and continuous integration/deployment. • Excellent problem-solving and debugging skills. • Strong communication and collaboration abilities to work effectively with cross-functional teams. Nice to Haves: • Advanced degree (Master's or Ph.D.) in Computer Science, Artificial Intelligence, or a related field. • Proven track record of implementing and deploying large-scale LLM systems in production environments. • Experience with distributed computing frameworks like Apache Spark or Hadoop. • Experience with natural language understanding, generation, and dialogue systems. • Familiarity with techniques such as transfer learning, few-shot learning, and reinforcement learning. • Contributions to open-source projects or research publications in the field of LLMs. • Experience with serving models using APIs and building scalable inference pipelines. • Knowledge of DevOps practices and tools like Docker, Kubernetes, and Jenkins. YOE Requirement: 12 yrs., B.S. in a technical discipline or 4 additional yrs. in place of B.S.