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.
As an Applied AI Finetuning Engineer, you will drive the adoption of frontier AI by developing bespoke and fine-tuned LLM solutions for top enterprises. You’ll leverage your customer-facing engineering experience and technical skills to help customize Anthropic's frontier LLMs to the needs of cutting-edge customer applications.
In collaboration with the Sales, Product, and Engineering teams, you’ll help enterprise partners incorporate leading-edge AI systems into their products. You will employ your excellent communication skills to explain and demonstrate complex solutions persuasively to technical and non-technical audiences alike. You will play a critical role in identifying opportunities to innovate and differentiate our AI systems, while maintaining our best-in-class safety standards.
Responsibilities:
- Design and execute high-quality finetuning projects for critical customers, delivering customized AI solutions with exceptional reliability
- Collaborate closely with ML researchers to develop and implement cutting-edge finetuning techniques
- Leverage advanced machine learning skills to optimize finetuning strategies and enhance model performance
- Partner with account executives to understand customer requirements and develop tailored finetuning solutions
- Serve as the primary technical advisor for customers on finetuning projects, offering guidance on integration, deployment, and best practices
- Stay current with the latest advancements in AI and finetuning techniques for large language models
- Travel occasionally to customer sites for workshops and implementation support
- Establish a shared vision for creating solutions that enable beneficial and safe AI
- Lead the vision, strategy, and execution of innovative solutions that leverage our latest models’ capabilities
You may be a good fit if you have:
- 3+ years of experience training or finetuning deep learning models
- 2+ years of experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect, or Platform Engineer
- Designed novel and innovative solutions for technical platforms in a developing business area
- Strong technical aptitude to partner with engineers and strong proficiency in at least one programming language (Python preferred)
- Recent experience building production systems with large language models
- The ability to navigate and execute amidst ambiguity, and to flex into different domains based on the business problem at hand, finding simple, easy-to-understand solutions
- Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities
- Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders. You enjoy engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities
- Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems
- A love of teaching, mentoring, and helping others succeed
Deadline to apply: None. Applications will be reviewed on a rolling basis.
The expected salary range for this position is:
Annual Salary:
$250,000—$300,000 USD
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.
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.
Top Skills
What We Do
Anthropic is an AI safety and research company that’s working to build reliable, interpretable, and steerable AI systems. Our research interests span multiple areas including natural language, human feedback, scaling laws, reinforcement learning, code generation, and interpretability.