Technical Lead Manager, Applied AI

Job responsibilities

• Lead a team in the design and development of scalable software applications leveraging generative AI models. - Guide the team in rapidly developing new features and iterating based on evaluation results. - Collaborate with researchers and product managers to translate research advancements into tangible product features. - Oversee the optimization of software performance and ensure the reliability of deployed applications. - Champion the development of best practices for building and deploying generative AI applications. - Lead the architecture and development of new products & features from 0 to 1. - Mentor and develop team members, fostering a collaborative and high-performing environment. - Partner with PM team to qualify & size new project opportunities. Minimum qualifications:

• A bachelor degree in computer science, electrical engineering or equivalent experience. - 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript). - 5 years of experience in minimum of one ML field (eg. media generation, reinforcement learning, infrastructure etc.)

• 7+ years of experience leading technical projects and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning), including at least 5 years of experience in a people leadership role overseeing and guiding technical teams. Preferred qualifications:

• Experience with generative AI models and applications. - Contributions to open-source projects. - Experience with front-end development. - Proven experience in rapidly developing and shipping software products in a fast-paced, customer-facing startup-like environment, demonstrating adaptability to changing priorities. - Experience evaluating model performance, analyzing results, and implementing improvements. - Experience with cloud computing platforms and infrastructure (e.g., Google Cloud Platform, AWS, Azure). - Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Hugging Face, etc. ##