Machine Learning Engineer, Gemini

vor 2 Monaten


Zürich, Schweiz Google Inc. Vollzeit
Mid

Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.

Apply

  • Bachelor's degree in Computer Science or related technical field, or equivalent practical experience.
  • 2 years of experience with NLP/LLMs.
  • Experience with ML models, working with data, quality metrics, quality iterations.
Preferred qualifications:
  • Master's degree or PhD in ML.
  • Experience with RL modeling.
  • Experience with large-scale distributed model training, MLOps, ML infrastructure.
  • Strong collaboration and communication skills.
  • Strong track record of pushing state-of-the-art in ML (already in LLMs).
About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

A conversational AI tool that enables users to collaborate with generative AI and help augment their imagination, expand their curiosity, and enhance their productivity.

Responsibilities
  • Research and productionize state-of-the-art post-training and inference-time techniques.
  • Investigate the next generation of model improvements targeting short and mid-term time-horizons.
  • Collaborate and share results with the broader team.
  • Operate in a high-reward and fast-paced environment.
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