Applied AI Engineer, Beneficial Deployments (Lab Automation)
Anthropic
- Location
- Hybrid (London, England)
- Compensation
- £225k - £255k/yr
- Employment
- Full-time
- Level
- Senior Level
About the role
Anthropic's Beneficial Deployments team seeks an Applied AI Engineer to automate scientific experiments using Claude. The role involves integrating LLMs with lab hardware, driving product direction, and scaling impact through documentation and cookbooks for the global scientific community.
Skills
Benefits
- Parental leave
- Generous vacation
Perks
- Flexible working hours
- Hybrid Work
Full job details
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 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 Beneficial Deployments
Beneficial Deployments ensures AI reaches and benefits the communities that need it most. We partner with nonprofits, foundations, and mission-driven organizations to deploy Claude in education, global health, economic mobility, and life sciences — focusing on raising the floor for those who need it most.
About the Role
We're looking for an Applied AI Engineer to join our Beneficial Deployments, Life Sciences team. Our goal is for Claude to close the loop on scientific discovery, and a significant part of this is helping Claude to drive scientific hardware and software. You'll help deploy the Model Hardware Standard (MHS) to labs doing the world’s most important research. You’ll scale what you learn in the field by contributing back to the standard, building scalable assets, and driving associated internal product and research direction.
Responsibilities
- Work with labs to automate their experiments end-to-end with Claude - from advising, to prototyping, to writing production code.
- Drive product, engineering and research direction based on field experience - e.g. building evals to measure limitations of our models in the physical world (capabilities and safety), developing new features on MHS, etc.
- Scale your impact to the long tail of labs through reusable cookbooks, documentation, and other assets.
- Be an EMEA ambassador for Claude in the lab - you’ll both inspire and build trust with scientific audiences, from small settings to large conferences.
- This role will require significant travel
You Might Be a Good Fit If You Have
- Hands-on experience connecting software to lab robots and instruments (liquid handlers, plate readers, scheduling software, LIMS), ideally in an automated lab.
- Strong engineering skills: you can take an LLM-powered tool from prototype to production code, and write evals to measure its performance.
- A scientist's instinct for how experiments work: you can spot what's worth automating, and where AI might fail or be unsafe in the physical world.
- Experience working directly with external customers or partners in a technical role.
- Clear written and verbal communication: you’ll write docs other labs can use without you and give talks that inspire and earn researchers' trust.
- A scrappy mentality–comfortable wearing multiple hats, building from scratch, driving clarity in ambiguous situations, and doing whatever it takes to further the mission.
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.
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.
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.