Technical Lead Manager, Model Quality - Claude Code

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 the Role

We're looking for a Technical Lead Manager to build and lead the Model Quality engineering team within Claude Code. This team sits at the intersection of engineering and research, building the eval systems, data pipelines, and experimentation infrastructure that tell us where Claude's coding capabilities excel and where they fall short, and then closing those gaps.

As TLM, you'll be hands-on, setting technical direction, reviewing designs, and shipping code alongside your team — while also hiring, coaching, and growing a group of strong senior engineers who thrive in ambiguous, high-intensity environments. You'll be the connective tissue between Claude Code product priorities and Anthropic's research org, ensuring the team is building infrastructure that actually accelerates our research loop.

What you'll do

You'll own the technical roadmap for model quality infrastructure on Claude Code, including eval frameworks, experimentation tooling, data pipelines.  You will be accountable for the reliability and correctness of systems that researchers depend on daily. You'll hire and support a team of engineers and you'll partner closely with research leadership to translate open questions into engineering priorities, and with Claude Code product to ensure capability improvements show up in the product. And you'll stay close to the code!

You may be a good fit if you

• Have led engineering teams (as a manager or tech lead) building complex infrastructure — data platforms, ML tooling, eval systems, or research computing

• Are a strong IC engineer in your own right and want to stay technical

• Have operated in high-intensity, fast-iteration environments and know how to keep a team moving without burning out

• Are comfortable navigating ambiguity across organizational boundaries — you know how to align teams with different incentives on shared goals

• Are a power user of agentic coding tools and have real intuition for where models are strong and where they break

• Care deeply about correctness and reliability, and can instill that bar in a team

• Have 8+ years of engineering experience, including 2+ leading teams

Strong candidates may also have

• Built or maintained evaluation frameworks for ML systems

• Experience with reinforcement learning infrastructure

• A background in research computing, scientific infrastructure, or ranking and recommendation systems

• Experience with production ML monitoring and observability

• A strong quantitative foundation

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—$485,000 USD

Logistics

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. 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