Used Tools & Technologies
Not specified
Required Skills & Competences ?
ETL @ 3 Hiring @ 3 Communication @ 3Details
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. The team consists of researchers, engineers, policy experts, and business leaders working to build beneficial AI systems.
Responsibilities
- Conduct pretraining data research.
- Understand pretraining data trends and scaling laws.
- Optimize pretraining data mixes.
- Investigate potential new sources of data.
- Build research tools to better understand experimental results.
- Process and utilize pretraining data effectively.
Requirements
- Significant software engineering experience.
- Results oriented with flexibility and impact focus.
- Comfortable working in an empirical research environment.
- Care about societal impacts of their work.
Strong candidates may also have experience with:
- High performance, large-scale ML systems.
- Language modeling with transformers.
- Large-scale ETL.
- Designing ML experiments and researching ML fundamentals.
- Inspecting and iterating on data (e.g., ML competitions, Quantitative Finance).
Representative projects
- Comparing compute efficiency of different datasets.
- Creating multimodal datasets in consumable formats for models.
- Scaling data processing jobs to thousands of machines.
- Designing research tools for data ablation experiments.
- Creating interactive visualizations of semantic clusters in training data.
Logistics
- Requires at least a Bachelor's degree in a related field or equivalent experience.
- Hybrid location policy: staff expected to be onsite at least 25% of the time; some roles may require more.
- Visa sponsorship available with immigration lawyer support.
Benefits
- Competitive compensation and benefits.
- Optional equity donation matching.
- Generous vacation and parental leave.
- Flexible working hours.
- Collaborative office space in San Francisco.
Company culture
- Focus on large-scale AI research with high impact.
- Team values communication and empirical research.
- Emphasis on ethical and societal impacts of AI work.
- Encourages diverse perspectives and inclusive hiring.