Research Engineer, Astra Evals, DeepMind
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Minimum qualifications:
- Bachelor's degree in Computer Science, Machine Learning, a related technical field, or equivalent practical experience.
- 5 years of experience in Python and one or more general-purpose programming languages (C++, Java, Go).
- Experience building or evaluating agentic systems using orchestration frameworks (e.g., LangChain, AutoGen, CrewAI, Semantic Kernel) or custom Large Language Models (LLMs)-based control loops.
- Experience developing machine learning pipelines.
Preferred qualifications:
- Master's degree or PhD in Computer Science, Machine Learning, or a related field.
- Experience with and adoption of capabilities for AI-assisted coding tools.
- Experience publishing at conferences on the topic of agentic AI and multimodal large language models (LLMs).
- Experience with model evaluation frameworks and data analysis tools.
- Excellent problem-solving skills applicable to agentic AI workflows.
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 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.We are pushing the boundaries across multiple domains. Our global teams offer learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.
Responsibilities
- Evaluate frontier agentic capabilities for AI assistance.
- Analyze evaluation results.
- Set and steer the reward function in reinforcement learning to improve Google's agentic capabilities.
- Transform friction points within agentic journeys into trainable examples.
- Provide insights to model and product teams.
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