Software Engineer, Research Productivity
- Salary
- $405,000 - $625,000
- Level
- Mid
- Visa
- Sponsors visas
Not stated in the posting: work type.
Open. First seen 20 September 2026.
About the role
Anthropic's standard text
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
Anthropic's Research Productivity organization builds the infrastructure and systems that accelerate research across Anthropic, including the tools that help our research process get faster and more effective over time. We're looking for an experienced software engineer to join us as we scale this infrastructure at a moment when both demand and scope are growing extremely quickly.
This team operates like a startup within a startup. You'll be a strong fit if you like thinking from first principles, iterating fast on infrastructure, and tackling reliability and scalability challenges head-on as the products built on top of your systems evolve underneath you.
You'll independently scope complex, multi-month projects, drive cross-org alignment through ambiguous problem spaces, and make the architectural decisions that shape how the infrastructure behind our research tooling gets built. You'll partner directly with research teams to understand their workflows, anticipate how their requirements will change, and design and scale infrastructure that can keep pace.
Responsibilities
- Design, build, and scale infrastructure and systems that support rapidly increasing usage, where requirements and workload continue to evolve as the products built on top of them evolve
- Independently scope and lead complex, multi-month engineering projects, from an ambiguous starting point through to a production system
- Drive cross-organizational alignment on technical direction, working through ambiguous problem spaces with multiple stakeholders and teams
- Make architectural decisions that shape the foundation of research infrastructure and tooling across Anthropic
- Partner directly with researchers to deeply understand their workflows, then anticipate and design for how those needs will change
- Iterate quickly, favoring pragmatic, first-principles solutions and fast feedback loops over heavy upfront design
- Take ownership of the reliability and scalability of critical systems as load, usage, and complexity increase
- Help set technical standards and best practices for the team, and mentor other engineers
Minimum Qualifications
- Experience designing, building, and operating large-scale distributed systems or infrastructure in production
- A track record of independently scoping and delivering complex, ambiguous, multi-month technical projects
- Strong software engineering fundamentals and hands-on coding ability
- Experience making architectural decisions that other engineers and teams build on top of
- Strong written and verbal communication skills, with experience driving alignment across multiple teams or stakeholders
- Demonstrated ability to operate effectively in ambiguous, fast-changing environments
Strong candidates may also have
- Experience building infrastructure or platforms specifically for research or machine learning workflows
- Direct experience navigating the reliability and architectural challenges that come with rapidly scaling systems
- Experience with distributed systems, cloud infrastructure, and infrastructure-as-code
- Familiarity with the compute, tooling, and workflow needs of large-scale machine learning research
- Experience operating in a startup or startup-like environment, i.e. a small, fast-moving team with high autonomy
- Prior experience as a technical lead or mentor for other engineers
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:
$405,000—$625,000 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.
Anthropic's standard text
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
Anthropic's standard text
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 this role asks for
63% of this description is written for the role. The rest is Anthropic's standard text, folded away below.
Read against Anthropic's other open postings on this site.
The team: AI Research & Engineering HIRES STEADILY
This role is one of 55 open in AI Research & Engineering. 4 were posted in the last 30 days and the oldest in April: a team that hires all year rather than one being built.
WHAT THE TEAM WORKS WITH, ACROSS ITS POSTINGS
LLM (39 of 55), Machine Learning (39 of 55), Python (32 of 55), PyTorch (15 of 55), Kubernetes (12 of 55), Rust (10 of 55), C++ (7 of 55)
OTHER ROLES ON THIS TEAM
- Staff Research Engineer, Multi-Agent Scaling posted Oct 2
- Software Engineer, Sandboxing posted Oct 1
- Research Engineer / Research Scientist, RL Frontiers posted Sep 29
- Research Engineer / Performance Engineer, RL Distributed Systems posted Sep 29
- Software Engineer, Tokens and Prompt Structures posted Sep 16
- Staff Software Engineer, Search posted Sep 11
- Performance Engineer, Inference Engine posted Sep 9
- Product Manager, Claude Science posted Aug 31
- Staff+ Research Engineer, RL Data Platform posted Aug 27
- Engineering Manager, Search posted Aug 3
- Staff Software Engineer, Code RL posted Jul 25
- Staff Software Engineer, Environments Infrastructure posted Jul 24
- Machine Learning Infrastructure Engineer, Safeguards Research posted Jul 21
- Research Engineer, Chip Design RL (Reinforcement Learning) posted Jul 13
- Engineering Manager, Research Data Platform posted Jul 7
- Research Engineer, Life Sciences posted Jul 3
- Research Engineer, Computer Use posted Jun 30
- Research Engineer, RL Scaling Science posted Jun 22
- Research Engineer, Code RL (Reinforcement Learning) posted Jun 11
- Data Operations Manager, Human Data posted Jun 3
- Product Engineer, Computer Use posted Jun 2
- Engineering Manager, Research Productivity posted May 22
- Performance Engineer, Inference Systems posted May 20
- Research Engineer, Post-Training Model Evaluations posted Apr 28
- Research Engineer, Machine Learning (RL Velocity) posted Apr 23
- Research Engineer, Machine Learning (RL Velocity) posted Apr 23
- Full-Stack Software Engineer, Reinforcement Learning posted Apr 14
- Anthropic Fellows Program, ML Systems & Reinforcement Learning posted Apr 10
- Anthropic Fellows Program, AI Safety & Security posted Apr 10
- Research Engineer, Pretraining posted Feb 17
- Research Engineer, Production Model Post-Training posted Feb 12
- Research Engineer, Machine Learning (Reinforcement Learning) posted Feb 11
- Research Engineer, Visual Knowledge Work posted Jan 16
- Research Engineer, Cybersecurity RL (Reinforcement Learning) posted Dec 9
- Software Engineer, Research Tools posted Nov 8
- Research Engineer, Interpretability posted Nov 7
- Pre-training Data Infrastructure Engineer posted Nov 3
- Research Engineer, RL Engineering posted Oct 15
- Research Engineer / Research Scientist, Tokens posted Oct 10
- ML/Research Engineer, Safeguards posted Oct 9
- Research Engineer, Pretraining Scaling - London posted Sep 30
- Research Engineer, Pretraining Scaling posted Sep 30
- Performance Engineer, GPU posted Sep 22
- Research Engineer/Research Scientist, Pre-training posted Jul 18
- Engineering Manager, GPU (ML Accelerator) posted May 29
- TPU Kernel Engineer posted May 22
- Research Engineer, Discovery posted May 14
- Staff Research Engineer, Discovery Team posted Apr 23
- Research Engineer / Scientist, Alignment posted Apr 14
- Research Engineer, Production Model Post-Training posted Apr 1
- Research Engineer, Machine Learning (Reinforcement Learning) posted Apr 1
- [Expression of Interest] Research Engineer / Scientist, Alignment - London posted Mar 31
- Research Engineer, Knowledge Team posted Apr 23
- Performance Engineer posted Apr 22
From the team and dates on Anthropic's own job board.
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