Bachelor's degree or equivalent practical experience.
8 years of experience in software development and with data structures/algorithms.
5 years of experience building and architecting large-scale, production quality Machine Learning (ML) systems.
5 years of experience with AI/ML algorithms and tools, Large Language Models (LLM) or other multimodal foundation models, and natural language processing.
5 years of experience in distributed development and large-scale data processing.
Experience coding in either C++ or Python.
Nice to haves:
3 years of experience in building model optimization pipelines using quantization and distillation techniques.
3 years of experience integrating ML, neural networks, including sequence/transformer modeling in other domains like perception or speech, or Generative AI into commercial products.
Experience in a technical leadership role leading project teams and setting technical direction.
Experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
Ability to contribute in the Machine Learning (ML) community through publications, open-source contributions, or conference participation.
What you'll be doing:
Drive the platform goal to incorporate fine-tuning, multi-agent systems, prompt engineering, model optimization into the Google product development lifecycle.
Develop and maintain our products, written in C++ and Python and ensure it complies with Google-wide coding and testing standards.
Design and implement customer requested Generative AI features through multiple stages, requirements gathering, proposing design and building agreement among the key stakeholders.
Collaborate with stakeholders, including other Google product areas, Google Research, and DeepMind organizations to identify emerging technology related to Artificial Intelligence (AI) and Generative AI and develop a strategic plan for translating these into practical solutions for Google products.
Provide technical leadership and mentorship to team members, fostering their growth and development in the applied Machine Learning (ML) space.
Perks and benefits:
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