Research Engineer, Model Lifecycle Engineering, Robotics, Datasets, DeepMind
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Minimum qualifications:
- Bachelor's degree in Computer Science, Mathematics, or a related field, or equivalent practical experience.
- 1 year of experience in Python.
- 1 year of experience with machine learning frameworks (e.g., JAX, PyTorch).
- Experience with machine learning and statistics.
Preferred qualifications:
- 1 year of C++ experience.
- Experience with profiling and performance analysis.
- Experience with robotics.
- Experience with designing and implementing large-scale distributed systems.
About the job
At Google, research-focused Software Engineers are embedded throughout the company, allowing them to setup large-scale tests and deploy promising ideas quickly and broadly. Ideas may come from internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.
From creating experiments and prototyping implementations to designing new architectures, engineers work on real-world problems including artificial intelligence, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. But you stay connected to your research roots as an active contributor to the wider research community by partnering with universities and publishing papers.
Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.
Responsibilities
- Collaborate with researchers and engineers to develop and maintain Gemini Robotics dataset infrastructure for training and evaluation.
- Build dataset pipelines to accelerate research.
- Implement, train, and evaluate large models and algorithms for robotic agents.
- Conduct dataset analysis and ablations for scaling Gemini Robotics models.
- Work effectively with a large collaborative team with fast-paced agendas to meet ambitious research goals.
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