Anthropic - Research Engineer, Reward Models Platform
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Requirements
• Location-based hybrid policy: • 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. • Visa sponsorship: • 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. 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 encourage you to apply even if you do not believe you meet every single qualification. • Your safety matters to us. • How we're different • 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! • 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 • Guidance on Candidates' AI Usage:
Responsibilities
• Design and build infrastructure that enables researchers to rapidly iterate on reward signals, including tools for rubric development, human feedback data analysis, and reward robustness evaluation • Develop systems for automated quality assessment of rewards, including detection of reward hacks and other pathologies • Create tooling that allows researchers to easily compare different reward methodologies (preference models, rubrics, programmatic rewards) and understand their effects • Build pipelines and workflows that reduce toil in reward development, from dataset preparation to evaluation to deployment • Implement monitoring and observability systems to track reward signal quality and surface issues during training runs • Collaborate with researchers to translate science requirements into platform capabilities • Optimize existing systems for performance, reliability, and ease of use • Contribute to the development of best practices and documentation for reward development workflows • You may be a good fit if you • Have prior research experience • Are excited to work closely with researchers and translate ambiguous requirements into well-scoped engineering projects • Have strong Python skills • Have experience with ML workflows and data pipelines, and building related infrastructure/tooling/platforms • Are comfortable working across the stack, ranging from data pipelines to experiment tracking to user-facing tooling • Can balance building robust, maintainable systems with the need to move quickly in a research environment • Are results-oriented, with a bias towards flexibility and impact • Pick up slack, even if it goes outside your job description • Care about the societal impacts of your work and are motivated by Anthropic's mission to develop safe AI • Strong candidates may also have experience with • Experience with ML research • Building internal tooling and platforms for ML researchers • Data quality assessment and pipeline optimization • Experiment tracking, evaluation frameworks, or MLOps tooling • Large-scale data processing (e.g., Spark, Hive, or similar) • Kubernetes, distributed systems, or cloud infrastructure • Familiarity with reinforcement learning or fine-tuning workflows • Representative projects • Building infrastructure that allows researchers to rapidly test new rubric designs against small models before scaling up • Developing automated systems to detect reward hacks and surface problematic behaviors during training • Creating tooling for comparing different grading methodologies and understanding their effects on model behavior • Building a data quality flywheel that helps researchers identify problematic transcripts and feed improvements back into the system • Developing dashboards and monitoring systems that give researchers visibility into reward signal quality across training runs • Streamlining dataset preparation workflows to reduce latency and operational overhead
Benefits
• 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. • $350,000 - $500,000 USD • Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. • 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. 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 • Create a Job Alert • Interested in building your career at Anthropic? Get future opportunities sent straight to your email.
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