Engineering Manager, SambaNova Systems

• Master's or PhD in a quantitative field such as Machine Learning and Computer Science
• 8+ years of experience in Machine Learning and Natural Language Processing, with 2+ years of experience with LLMs
• 2+ years proven success in leading and managing a team of 5 or more engineers, driving their professional growth and delivering impactful projects
• Proficiency in Python, with hands-on experience using machine learning libraries and frameworks such as Pytorch, Tensorflow, or JAX
• Strong communication and collaboration skills, with the ability to effectively convey technical concepts to both technical and non-technical stakeholders in a fast-paced context
• Proven track record of managing complex machine learning projects end to end and driving research ideas to production

Desirable

• We are looking for a world-class engineering leader to manage a team of talented Machine Learning engineers and researchers driving the development & innovation around our LLMs
• You'll work closely with cross-functional teams to optimize performance and drive velocity
• Lead and manage a high-performing team of 8-10 ML engineers and researchers in a fast-paced environment, providing technical guidance, mentorship, and support to drive their professional growth and development
• Oversee the rapid development and implementation of LLMs, leveraging advanced algorithms and techniques to improve accuracy and optimize performance
• Collaborate closely with cross-functional teams, including product managers and infrastructure teams to deliver insights and recommendations for Product and ML Roadmap
• Define processes to drive research and enable faster execution
• Stay at the forefront of industry trends, emerging technologies, and best practices in machine learning, foundation models and deep learning. Apply this knowledge to drive innovation, meet tight deadlines, and maintain a competitive edge
• Drive project execution by goal setting and project management
• Establish and maintain strong relationships with stakeholders, providing clear communication of technical concepts and findings to both technical and non-technical audiences
• Lead recruiting, onboarding, performance management, goal setting and related processes for the team