We are seeking a highly motivated and innovative Software Engineer to join us in rapidly exploring and implementing the state-of-the-art Gemini models across core Google products. You will work directly with engineering, product, and research teams to quickly ideate, build, and iterate on proof-of-concept integrations that leverage cutting-edge AI capabilities.
This role is about moving fast to validate new ideas, utilizing the latest advancements in multimodal large language models (vision, audio, text) to build functional, tangible prototypes. You will need to be a flexible, full-stack thinker, capable of jumping between different parts of the stack,from hacking together an agent harness for Gemini to quickly bringing up an end-to-end application demo for proving out product experiences.
In this role, you will apply your broad engineering expertise to create the initial sparks that could eventually impact users globally.
As a Software Engineer at Google DeepMind, you will be at the forefront of translating research into tangible product concepts. You will drive the rapid development of experimental Gemini-powered features, pushing the boundaries of what's possible to create novel agentic services and “zero-to-one” engaging user experiences.
Further, you will be collaborating with multiple product surfaces across Google to bring to life some of these experiences.
You are a passionate and talented software engineer with a versatile, full-stack AI skillset and a proven ability to rapidly prototype and iterate on ideas. You have a collaborative mindset and are excited to work as part of a team to tackle ambitious, undefined challenges.
You are passionate about seeing AI research translated into real-world product concepts and are eager to work in an environment where speed of experimentation is key to long-term impact. You are a flexible thinker who can creatively solve problems up and down the stack to get compelling demos and experiences working in product form factor.
A Bachelor's, Master's, or Ph.D. in Computer Science, Artificial Intelligence, or a related field is required. A minimum of 5 years of relevant professional experience is also required.
Experience with core software engineering and building highly available, high-traffic production systems is necessary. Experience training, deploying, and operating large machine learning models (LLMs or similar) in a high-scale, low-latency production environment is also required.
Solid understanding of distributed systems, cloud computing principles, and performance optimization is necessary. Proven track record in 'zero-to-one' development,transforming raw ideas into rapid prototypes and full stack experience driving them through to full production,is also required.
Strong programming skills in Python and C++ are necessary. Experience with relevant ML frameworks such as JAX, TensorFlow, or PyTorch, particularly for inference and serving, is also required.
Excellent communication and collaboration skills are necessary.
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