at Anthropic
Location
New York City, NY; San Francisco, CA; Seattle, WA
Compensation
$350k–$850k USD
Type
full time
Posted
5 months ago
Remote
Yes
Market range · company + function + seniority
p25 · target · p75 · n=89
Posted $850k · in the market band
Posting health
Aging · 65Tailor your résumé to this role in 30 seconds.
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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.
We’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 like 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, finetuning, 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
Finetuning 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 listed 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.
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
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 application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
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