Key responsibilities
Design and implement evaluation methodologies for assessing AI model capabilities relevant to engineering and applied science research and applications
Design realistic tasks and training environments, and curate data from your field
Develop and validate simulations and computational tools for your field, and calibrate them against real-world data
Work with industry partners, manufacturers, and labs to build and test what Claude invents, designs, and engineers, and bring that real-world feedback into evaluation and training
Think through how Claude's engineering capabilities can permeate the real world: where they can have the most impact across industry and research, and what it takes to get them adopted
Advise the team on which problems, tools, and workflows matter most in your field
Collaborate with domain experts and partners to establish benchmarks and gather high-quality data for training
Translate between engineering domain knowledge and machine learning objectives
Minimum qualifications
Deep expertise and hands-on R&D or industry experience in an engineering or applied science discipline, such as mechanical, electrical, materials, chemical, aerospace, structural, industrial, or manufacturing engineering; applied physics; computational simulation
Experience with AI or machine learning, whether evaluating and training AI systems or applying these tools in your field
Track record of taking work from concept through to a working result, such as a product, process, device, experiment, or tool
Hands-on proficiency with the computational design, analysis, or simulation tools used in your field
Basic programming proficiency, for example in Python
Ability to navigate ambiguity and develop solutions in a rapidly evolving research environment
Ability to work independently while collaborating closely with cross-functional teams, and to explain your field clearly to people outside it
Commitment to using AI to accelerate engineering and scientific progress while maintaining high ethical standards
Preferred qualifications
5+ years of hands-on R&D or industry experience in an engineering or applied science discipline
Ph.D. in an engineering or applied science field, or equivalent industry experience
Industry experience in product design and manufacturing, or in developing engineering or scientific simulation software
Breadth across more than one discipline, or across several stages of the path from design to production
Familiarity with modern AI model training methods
Track record of building high-fidelity solvers or simulation engines that were validated against real-world data and used in practice
Experience working with manufacturers, vendors, contract research organizations, or academic labs
Experience managing data pipelines and working with large-scale technical datasets
Publications, patents, or contributions to open-source scientific or engineering software
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.
Annual Salary
$320,000—$405,000 USD
Logistics
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.
For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
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.
How we're different
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.
Come work with us!
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.
