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Research Engineer / Research Scientist, Pre-training(m/w/x)
Developing multimodal architectures and data processing optimizers for large-scale model training. Expertise in Python, deep learning, and ML accelerators required. Optional equity donation matching and generous parental leave.
Anforderungen
- Degree (BA required, MS or PhD preferred) in Computer Science, Machine Learning, or related field
- Strong software engineering skills; proven track record building complex systems
- Expertise in Python and deep learning frameworks
- Experience with high-performance, large-scale ML systems, language modeling
- Familiarity with ML Accelerators, Kubernetes, large-scale data processing
- Strong problem-solving skills and results-oriented mindset
- Excellent communication skills and collaborative work ability
- Significant software engineering experience
- Ability to balance research goals with practical engineering constraints
- Willingness to take on tasks outside job description
- Enjoyment of pair programming and collaborative work
- Eagerness to learn about machine learning research
- Enthusiasm for working in a cohesive team on large-scale AI research
- Ambitious goals for AI safety and long-term progress
- At least a Bachelor's degree in a related field or equivalent experience
Aufgaben
- Conduct research on model architecture, algorithms, data processing, and optimizers
- Implement solutions for model architecture, algorithms, data processing, and optimizers
- Lead small research projects independently
- Collaborate with team members on larger initiatives
- Design, run, and analyze scientific experiments
- Optimize and scale training infrastructure for efficiency and reliability
- Develop and improve dev tooling for team productivity
- Contribute to the entire stack, from optimization to model design
- Optimize throughput of novel attention mechanisms
- Propose Transformer variants
- Experimentally compare Transformer variant performance
- Prepare large-scale datasets for model consumption
- Scale distributed training jobs to thousands of accelerators
- Design fault tolerance strategies for training infrastructure
- Create interactive visualizations of model internals
Berufserfahrung
- ca. 1 - 4 Jahre
Ausbildung
- Bachelor-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Python
- deep learning frameworks
- ML systems
- language modeling
- ML Accelerators
- Kubernetes
Benefits
Attraktive Vergütung
- Competitive compensation
Gemeinnützige Ausrichtung
- Optional equity donation matching
Mehr Urlaubstage
- Generous vacation
Großzügige Elternzeit
- Generous parental leave
Flexibles Arbeiten
- Flexible working hours
Modernes Büro
- Collaborative office space
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- AnthropicVollzeitmit HomeofficeBerufserfahrenZürich
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Research Engineer / Research Scientist, Pre-training(m/w/x)
Developing multimodal architectures and data processing optimizers for large-scale model training. Expertise in Python, deep learning, and ML accelerators required. Optional equity donation matching and generous parental leave.
Anforderungen
- Degree (BA required, MS or PhD preferred) in Computer Science, Machine Learning, or related field
- Strong software engineering skills; proven track record building complex systems
- Expertise in Python and deep learning frameworks
- Experience with high-performance, large-scale ML systems, language modeling
- Familiarity with ML Accelerators, Kubernetes, large-scale data processing
- Strong problem-solving skills and results-oriented mindset
- Excellent communication skills and collaborative work ability
- Significant software engineering experience
- Ability to balance research goals with practical engineering constraints
- Willingness to take on tasks outside job description
- Enjoyment of pair programming and collaborative work
- Eagerness to learn about machine learning research
- Enthusiasm for working in a cohesive team on large-scale AI research
- Ambitious goals for AI safety and long-term progress
- At least a Bachelor's degree in a related field or equivalent experience
Aufgaben
- Conduct research on model architecture, algorithms, data processing, and optimizers
- Implement solutions for model architecture, algorithms, data processing, and optimizers
- Lead small research projects independently
- Collaborate with team members on larger initiatives
- Design, run, and analyze scientific experiments
- Optimize and scale training infrastructure for efficiency and reliability
- Develop and improve dev tooling for team productivity
- Contribute to the entire stack, from optimization to model design
- Optimize throughput of novel attention mechanisms
- Propose Transformer variants
- Experimentally compare Transformer variant performance
- Prepare large-scale datasets for model consumption
- Scale distributed training jobs to thousands of accelerators
- Design fault tolerance strategies for training infrastructure
- Create interactive visualizations of model internals
Berufserfahrung
- ca. 1 - 4 Jahre
Ausbildung
- Bachelor-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Python
- deep learning frameworks
- ML systems
- language modeling
- ML Accelerators
- Kubernetes
Benefits
Attraktive Vergütung
- Competitive compensation
Gemeinnützige Ausrichtung
- Optional equity donation matching
Mehr Urlaubstage
- Generous vacation
Großzügige Elternzeit
- Generous parental leave
Flexibles Arbeiten
- Flexible working hours
Modernes Büro
- Collaborative office space
Über das Unternehmen
Anthropic
Branche
Science
Beschreibung
The company aims to create reliable, interpretable, and steerable AI systems for safe and beneficial use.
Noch nicht perfekt?
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