Software Engineering Manager, GenAI, Computer Vision, Google Maps Immersive Navigation

Job description

Take end-to-end ownership of converting complex imagery, location, and sensor data into precise geometries to power Geo’s next generation navigation products. Translate ambiguous input data challenges into clear algorithmic, ML, GenAI formulations, brainstorming directly with product, UX, and engineering to define the optimal visual experience and iterate towards scalable solutions. Set and communicate team priorities that support the broader organization's goals. Align strategy, processes, and decision-making across teams. Set clear expectations with individuals based on their level and role, aligned with broader organizational goals. Meet regularly with individuals to discuss performance, development, feedback and coaching. Develop the long-term technical outlook and roadmap, meeting anticipated future requirements and infrastructure needs. Design, guide and vet system designs, and write product or system development code to solve ambiguous problems. Conduct code reviews and provide feedback ensuring best practices. Minimum Qualifications: Bachelor’s degree, or equivalent practical 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 a technical leadership role; overseeing projects, with 3 years of experience in a people management, supervision/team leadership role. 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). Experience with computer vision learning techniques, machine learning algorithms (supervised and unsupervised learning, deep learning, reinforcement learning), generative AI, or applied AI applications Preferred Qualifications: Master's degree or PhD in Computer Science, or a related technical field. 5 years of experience with one or more of the following: Computer Vision, Reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field. Multiple research publications in top CV/ML conferences (e.g., CVPR/ICCV/ECCV/NIPS/ICLR). Experience working in large-sized engineering and cross-functional teams. Expertise in modeling with TensorFlow, JAX, etc. Excellent people management and communication skills.