Research Engineer, Production Model Post-Training

ph3bAbout Anthropic /b /h3 pAnthropic’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. /p h3bAbout the role /b /h3 pAnthropic's production models undergo sophisticated post-training processes to enhance their capabilities, alignment, and safety. As a Research Engineer on our Post-Training team, you'll train our base models through the complete post-training stack to deliver the production Claude models that users interact with. /p pYou'll work at the intersection of cutting-edge research and production engineering, implementing, scaling, and improving post-training techniques like Constitutional AI, RLHF, and other alignment methodologies. Your work will directly impact the quality, safety, and capabilities of our production models. /p pNote: For this role, we conduct all interviews in Python. This role may require responding to incidents on short-notice, including on weekends. /p h3bResponsibilities: /b /h3 ul liImplement and optimize post-training techniques at scale on frontier models /li liConduct research to develop and optimize post-training recipes that directly improve production model quality /li liDesign, build, and run robust, efficient pipelines for model fine-tuning and evaluation /li liDevelop tools to measure and improve model performance across various dimensions /li liCollaborate with research teams to translate emerging techniques into production-ready implementations /li liDebug complex issues in training pipelines and model behavior /li liHelp establish best practices for reliable, reproducible model post-training /li /ul h3bYou may be a good fit if you: /b /h3 ul liThrive in controlled chaos and are energised, rather than overwhelmed, when juggling multiple urgent priorities /li liAdapt quickly to changing priorities /li liMaintain clarity when debugging complex, time-sensitive issues /li liHave strong software engineering skills with experience building complex ML systems /li liAre comfortable working with large-scale distributed systems and high-performance computing /li liHave experience with training, fine-tuning, or evaluating large language models /li liCan balance research exploration with engineering rigor and operational reliability /li liAre adept at analyzing and debugging model training processes /li liEnjoy collaborating across research and engineering disciplines /li liCan navigate ambiguity and make progress in fast-moving research environments /li /ul h3bStrong candidates may also: /b /h3 ul liHave experience with LLMs /li liHave a keen interest in AI safety and responsible deployment /li /ul pWe welcome candidates at various experience levels, with a preference for senior engineers who have hands‑on experience with frontier AI systems. However, proficiency in Python, deep learning frameworks, and distributed computing is required for this role. /p h3bLogistics /b /h3 pbEducation requirements: /b We require at least a Bachelor's degree in a related field or equivalent experience. /p pbLocation‑based hybrid policy: /b 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. /p pbVisa sponsorship: /b 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. /p pbWe encourage you to apply even if you do not believe you meet every single qualification. /b 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. /p pbYour safety matters to us. /b 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. /p h3bHow we're different /b /h3 pWe 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. /p pThe 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. /p h3bCome work with us! /b /h3 pAnthropic 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. bGuidance on Candidates' AI Usage: /b Learn about our policy for using AI in our application process. /p /p #J-18808-Ljbffr