Research Engineer/Research Scientist, Vision , NY; San Francisco, CA; Seattle, WA
Listed on 2026-03-01
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Software Development
Data Scientist, AI Engineer, Machine Learning/ ML Engineer
Research Engineer / Research Scientist, Vision About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the roleWe’re looking for research engineers with a strong computer vision background who believe that visual and spatial reasoning are core to fully unlocking the capabilities of LLMs. In this role, you'll work on research, development, and evaluation for state‑of‑the‑art Claude models, with a focus on visual and spatial capabilities. This role is highly collaborative and will touch many aspects of our broader research efforts, taking a full‑stack approach across pretraining, RL, and runtime techniques such as agentic harnesses.
Additionally, you’ll partner with the product org to ensure that the vision improvements you deliver impact Claude’s performance on real‑world tasks.
- Run experiments to evaluate architectural variants, data strategies, and SL and RL techniques to improve Claude’s vision
- Develop and test tools, skills, and agentic infrastructure that enable Claude to reason over visual inputs
- Create evaluations and benchmarks that measure progress on multimodal capabilities across training and deployment
- Work with our product org to find solutions to our most vexing API customer challenges related to vision and spatial reasoning
- Have 7+ years of ML, computer vision, and software engineering experience through industry, academia, or other projects
- Are familiar with the architecture, training, and operation of large vision‑language models
- Have experience creating and evaluating large synthetic and real‑world visual training datasets
- Have experience engaging in systematic prompting, fine tuning, or evaluation
- Are results‑oriented, with a bias towards flexibility and impact
- Enjoy pair programming and cross‑team collaboration
- Care about the societal impacts of your work
- Large‑scale pretraining, SL, and RL on language models
- Deep learning research on images, video, or other modalities
- Developing complex agentic systems using LLMs
- High‑performance ML systems (GPUs, TPUs, JAX, PyTorch)
- Large‑scale ETL and data pipeline development
- Running experiments to determine ideal training datamixes and parameters for a synthetically generated vision dataset
- Fine tuning Claude to maximize its performance using a particular set of agent tools/skills
- Building a pipeline to ingest and process a novel source of visual training data
- Designing and running experiments to evaluate the scalability of two architectural variants
The annual compensation range for this role is below. For sales roles, the range provided is the role’s On Target Earnings (“OTE”) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Our total compensation package for full‑time employees includes equity and benefits.
$350,000 – $850,000 USD
LogisticsEducation requirements: We require at least a Bachelor’s degree in a related field or equivalent experience.
Location‑based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren’t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an…
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