AI Insights
Anthropic

Technical Lead Manager, Model Quality - Claude Code

Anthropic · San Francisco, California, US
full-timelead (8-20 yrs)Posted 47d ago
Engineering LeadershipM1IC + ManagementHybrid (1d)Visa Sponsored
StackPythonML evaluation frameworksData pipelinesReinforcement learning infrastructureResearch computingML monitoringObservability toolingExperimentation infrastructureAgentic coding toolsQuantitative analysisSystem designDistributed systems

Summary

Anthropic is seeking a Technical Lead Manager to build and lead the Model Quality engineering team within Claude Code, owning eval frameworks, data pipelines, and experimentation infrastructure that drive Claude's coding capability improvements. The role blends hands-on engineering with people leadership at the frontier of AI development.

About the role

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

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

What you'll do

1Own the technical roadmap for model quality infrastructure on Claude Code, including eval frameworks, experimentation tooling, and data pipelines
2Ensure reliability and correctness of systems that researchers depend on daily
3Hire, coach, and grow a team of senior engineers who thrive in ambiguous, high-intensity environments
4Partner with research leadership to translate open research questions into actionable engineering priorities
5Collaborate with Claude Code product team to ensure capability improvements surface in the product
6Stay hands-on with code, reviewing designs, and setting technical direction alongside the team
7Serve as connective tissue between Claude Code product priorities and Anthropic's research organization

Requirements

8+ years of engineering experience including 2+ years leading engineering teams, with a strong IC foundation and desire to stay technical
Proven track record building complex infrastructure such as data platforms, ML tooling, eval systems, or research computing at scale
Demonstrated ability to operate in high-intensity, fast-iteration environments while maintaining team health and execution quality
Experience navigating cross-organizational ambiguity and aligning teams with different incentives around shared technical goals
Power-user familiarity with agentic coding tools and deep intuition for model strengths and failure modes

Nice to have

Reinforcement learning infrastructure
ML evaluation framework design
Research computing
Scientific infrastructure
Ranking and recommendation systems
Production ML monitoring
ML observability

Role overview

Role family
Engineering Leadership
Level
M1 — ml_ai
Experience
8–20 years
Type
Hybrid (IC + Management)
Remote policy
Hybrid (1 days)
Visa sponsorship
Available

Tech stack analysis

LANGUAGES
Python
FRAMEWORKS
ML evaluation frameworksReinforcement learning pipelines
INFRASTRUCTURE
Data pipelinesExperimentation infrastructureML monitoring systemsResearch computing clusters
TOOLS
Agentic coding tools (e.g., Claude Code)ML observability tooling

Green flags

6 items
Salary range explicitly disclosed ($320K–$485K), which is rare and signals candidate respect and transparencytransparency

Discover all 6 green flags for this role

Sign up free →

Benefits breakdown

HEALTH & WELLNESS
Not explicitly detailed, but Anthropic is known for strong health benefits packages

See all benefits organized by category — health, financial, time off & more

Sign up free →

Hiring insights

JD quality
9/10
Urgency
high
Autonomy
high
Team size
small (2-5) to medium (5-15) — team being built from scratch

See JD quality score, hiring urgency & team details

Sign up free →

Red flags

PRO4 items
'High-intensity, fast-iteration environment' language signals a demanding pace that may not suit everyonework life balance

See all 4 red flags — what the JD isn't telling you

Sign up free →

Interview insights

PRO
Rounds
5
Duration
4 wks
Difficulty
very hard
Take-home
Yes

Get full interview breakdown — rounds, likely topics & prep tips

Sign up free →

Career path

PRO
Next roles
Director of Engineering (Model Quality / Research Infra)VP of Engineering at AI companyHead of ML Infrastructure

See where this role leads — full career progression

Sign up free →
About the company

Anthropic is an AI safety company building Claude, one of the most capable large language models in the world. Founded by former OpenAI leaders, Anthropic focuses on developing reliable, interpretable, and steerable AI systems. The company has raised over $7 billion and partners with Amazon and Google on frontier AI research.

HQSan Francisco, CA, USA
Interview difficultyvery hard
Build vs Maintainbuild
Cross-functionalYes