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For Companies At a Glance
- Tasks: Design and optimise cutting-edge AI models for robots and devices.
- Company: Join Google DeepMind, a leader in AI innovation and ethics.
- Benefits: Competitive salary, bonuses, equity, and comprehensive benefits.
- Why this job: Make a real-world impact with your research in robotics and AI.
- Qualifications: PhD in relevant field and experience with deep learning frameworks.
- Other info: Diverse team culture with opportunities for growth and collaboration.
Snapshot
Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.
About Us
We are looking for Research Scientists to join the Robotics team whose mission is to build “Embodied AI” to power the next generation of helpful robots.
Job Summary
We are looking for a Research Scientist to join our robotics team and push the boundaries of on-device model optimization. You will work on developing novel end-to-end models, improving their accuracy, efficiency, and robustness for deployment on physical devices like GPUs and robots.
Responsibilities
- Design, train, and evaluate deep learning models for various on-device applications.
- Develop novel algorithms for improving model performance and efficiency, including but not limited to:
- End-to-end model architectures.
- Optimization techniques for inference on constrained hardware.
- Techniques for domain adaptation and semi-supervised learning.
- Confidence estimation and uncertainty modeling.
- Work on related machine learning tasks such as model compression, quantization, and efficient resource utilization.
- Optimize models for on-device and streaming applications, specifically considering latency, computational constraints, and deployment on physical devices such as GPUs, embedded systems, and robots.
- Collaborate with other researchers and engineers to integrate your work into products.
Minimum Qualifications
- PhD in Computer Science, Electrical Engineering, or a related field with a focus on machine learning, deep learning, or embedded systems, or equivalent practical experience.
- Experience with deep learning frameworks such as JAX or PyTorch.
- Strong programming skills in Python or C++.
- Experience with large-scale data and distributed training.
- Experience with on-device machine learning and model optimization for various hardware platforms, including GPUs, TPUs, and embedded systems.
- Experience with real-time systems and deployment on physical devices.
Preferred Qualifications
- A strong publication record in top-tier machine learning or systems conferences (e.g., NeurIPS, ICML, MLSys, CVPR, ICCV).
- A passion for solving challenging research problems and a desire to make a real-world impact.
The US base salary range for this full-time position is between $248,000 – $349,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.
At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunities regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.
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Research Scientist, Model Optimization employer: The Rundown AI, Inc.
Contact Detail:
The Rundown AI, Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Scientist, Model Optimization
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, conferences, or even online webinars. We can’t stress enough how valuable it is to chat with people who are already in the field; they might just know about opportunities that aren’t advertised yet.
✨Show Off Your Skills
Don’t just tell them what you can do—show them! Create a portfolio of your projects, especially those related to model optimization or deep learning. We love seeing practical applications of your skills, so make sure to highlight any relevant work you've done.
✨Ace the Interview
Prepare for technical interviews by brushing up on your algorithms and coding skills. We recommend practicing common interview questions and even doing mock interviews with friends. Remember, confidence is key, so go in ready to showcase your expertise!
✨Apply Through Our Website
When you find a role that excites you, apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always on the lookout for passionate candidates who want to make a difference in AI.
We think you need these skills to ace Research Scientist, Model Optimization
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Research Scientist role. Highlight your experience with deep learning frameworks and any relevant projects that showcase your skills in model optimization. We want to see how your background aligns with our mission!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your expertise can contribute to our robotics team. Keep it engaging and personal – we love to see your personality come through!
Showcase Your Publications: If you've got a strong publication record, make sure to highlight it! Mention any top-tier conferences you've contributed to, as this shows your commitment to advancing the field. We appreciate candidates who are active in the research community.
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our team and culture!
How to prepare for a job interview at The Rundown AI, Inc.
✨Know Your Models Inside Out
Make sure you’re well-versed in the deep learning models and algorithms relevant to the role. Be prepared to discuss your past experiences with model optimization, including specific techniques you've used for improving performance on constrained hardware.
✨Showcase Your Programming Skills
Since strong programming skills in Python or C++ are crucial, brush up on your coding abilities. You might be asked to solve a problem on the spot, so practice coding challenges that relate to machine learning and model deployment.
✨Prepare for Technical Questions
Expect technical questions about on-device machine learning and real-time systems. Review concepts like model compression, quantization, and domain adaptation, and be ready to explain how you would apply these in practical scenarios.
✨Demonstrate Collaboration Skills
Collaboration is key in this role, so think of examples where you’ve worked with other researchers or engineers. Be ready to discuss how you integrated your work into larger projects and how you handle feedback and differing opinions.
