Machine Learning Software Engineer, Decision Forests
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Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 5 years of experience with software development in one or more programming languages.
- 2 years of experience with C++ and Python.
- Experience with machine learning/AI in a software development environment.
Preferred qualifications:
- 5 years of experience with data structures and algorithms.
- Experience with one or more neural network frameworks: PyTorch, TensorFlow or Jax.
- Experience with applied machine learning/machine learning research.
- Experience with decision trees.
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.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Responsibilities
- Take co-ownership of new feature development (e.g., design, implementation, UX experiments, maintenance), drive corresponding applied research (reading papers, experimentation and benchmarking, possibly attending/publishing-in conferences), client collaboration (ranging from small consultations to deep engagements), and collaboration with other researchers.
- Develop training capability on GPU and TPU of oblique, and other complex, forest models.
- Design and productionize continuous learning algorithms and other tools/capabilities to make models to data distribution drift, training data storage policies, prediction churn, and removal/update of input signal.
- Improve anomaly detection algorithms and productionize them into highly usable and integrated features.
- Interact and collaborate (e.g., brainstorming, cross-project collaboration) with other topics, notably graph neural networks and agents.
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Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
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