AI Researcher (Multimodal Perception Models)
TavusSalary not specified
Full Time
Expert & Leadership (9+ years)
Not SpecifiedCompensation
Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Artificial Intelligence, Machine Learning, TechnologyIndustries
Requirements
- BSc, MSc or PhD/DPhil degree in computer science, physics, mathematics, applied statistics, machine learning, or equivalent practical experience
- Strong background in deep learning, with proven experience with relevant architectures (e.g., Transformers, GNNs, etc.)
- Experience with training large-scale machine learning models, particularly in the multimodal domain (video, text)
- Excellent software engineering skills with a proven ability to build robust and scalable systems
- Proficiency with ML and scientific libraries such as JAX, TensorFlow, PyTorch, NumPy, and Pandas
- Experience with either large-scale data processing frameworks (e.g., Apache Beam, Spark) or distributed training infrastructure
- Exceptional programming and engineering skills
- Deep understanding of large-scale neural network training and data processing
- Strong working knowledge of machine learning experimentation
- Hands-on experience with training and developing multimodal models
Responsibilities
- Develop, maintain, and improve large-scale multimodal models, with a focus on video modeling, and the data pipelines for training and evaluation
- Design and implement novel methods for evaluating and improving multi-modal generative models, particularly at the post-training stage
- Build and maintain robust data pipelines for collecting and processing large-scale datasets, including human-labeled data
- Collaborate with research scientists to translate research ideas into production-ready code
Skills
Key technologies and capabilities for this role
Questions & Answers
Common questions about this position
What degree is required for the Research Engineer position?
A BSc, MSc, or PhD/DPhil in computer science, physics, mathematics, applied statistics, machine learning, or equivalent practical experience is required.
What technical skills and experience are essential for this role?
Candidates need a strong background in deep learning with experience in architectures like Transformers and GNNs, training large-scale multimodal models (especially video and text), proficiency in JAX, TensorFlow, PyTorch, NumPy, and Pandas, and experience with large-scale data processing or distributed training.
What are the key responsibilities of the Research Engineer?
Responsibilities include developing and improving large-scale multimodal models focused on video, designing evaluation methods for generative models, building data pipelines for large-scale datasets, and collaborating with scientists to productionize research ideas.
What is the company culture like at Google DeepMind?
Google DeepMind values diversity of experience, knowledge, backgrounds, and perspectives, fosters collaboration among scientists, engineers, and machine learning experts, and prioritizes safety, ethics, public benefit, and scientific discovery.
What makes a strong candidate for this Research Engineer role?
A strong candidate has exceptional programming skills, deep knowledge of large-scale neural network training and data processing, hands-on experience with multimodal models especially video, and excellent software engineering abilities for scalable systems.
DeepMind
Develops artificial general intelligence systems
About DeepMind
This company leads in the field of artificial general intelligence (AGI), with notable applications across healthcare, energy management, and biotechnology. Their work in early diagnostic tools for eye diseases, optimizing energy usage in major data centers, and groundbreaking contributions to protein structure prediction underlines their commitment to harnessing AI for diverse practical applications. The company's dedication to pushing the boundaries of AI technology not only propels the industry forward but also creates a dynamic and impactful working environment for its employees.
London, United KingdomHeadquarters
2010Year Founded
$4.9MTotal Funding
ACQUISITIONCompany Stage
AI & Machine Learning, BiotechnologyIndustries
1,001-5,000Employees
Benefits
Performance Bonus
Risks
Emerging AI models may challenge DeepMind's current strategies.
Backlash against AI models like Gemini poses reputational risks.
Labeling AI-generated content could increase operational complexity for DeepMind.
Differentiation
DeepMind combines AI, ML, and neuroscience for general-purpose learning algorithms.
DeepMind's AlphaFold model advances protein folding research significantly.
GraphCast by DeepMind offers rapid, accurate ten-day weather forecasts.
Upsides
AI-driven drug discovery is set to grow significantly in 2024.
AlphaCode 2 showcases AI's potential in competitive programming.
DeepMind's AI tools are transforming music creation and meteorology.
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