Staff Infrastructure Engineer, AI Scientist Team
Staff Infrastructure Engineer, AI Scientist Team
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$ 315000 - 560000
1 Vacancy
Job Description
About Anthropic
Anthropics 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
As a Staff Infrastructure Engineer on our team you will work end to end identifying and addressing key infra blockers on the path to scientific AGI. Strong candidates should have familiarity with performance optimization distributed systems vm/sandboxing/container deployment and large scale data pipelines. Familiarity with language model training evaluation and inference is highly encouraged.
Join us in our mission to develop advanced AI systems that are both powerful and beneficial for humanity.
Responsibilities:
- Design and implement largescale infrastructure systems to support AI scientist training evaluation and deployment across distributed environments
- Identify and resolve infrastructure bottlenecks impeding progress toward scientific capabilities
- Develop robust and reliable evaluation frameworks for measuring progress towards scientific AGI.
- Build scalable and performant VM/sandboxing/container architectures to safely execute longhorizon AI tasks and scientific workflows
- Collaborate to translate experimental requirements into productionready infrastructure
- Develop large scale data pipelines to handle advanced language model training requirements
- Optimize large scale training and inference pipelines for stable and efficient reinforcement learning
You may be a good fit if you:
- Have 3 years of highly relevant experience in infrastructure engineering with demonstrated expertise in largescale distributed systems
- Are a strong communicator and enjoy working collaboratively
- Possess deep knowledge of performance optimization techniques and system architectures for highthroughput ML workloads
- Have experience with containerization technologies (Docker Kubernetes) and orchestration at scale
- Have proven track record of building largescale data pipelines and distributed storage systems
- Excel at diagnosing and resolving complex infrastructure challenges in production environments
- Can work effectively across the full ML stack from data pipelines to performance optimization
- Have experience collaborating with other researchers to scale experimental ideas
Strong candidates may also have:
- Experience with language model training infrastructure and distributed ML frameworks (PyTorch JAX etc.)
- Background in building infrastructure for AI research labs or largescale ML organizations
- Knowledge of GPU/TPU architectures and language model inference optimization
- Experience with cloud platforms (AWS GCP) at enterprise scale
- Familiarity with VM and container orchestration.
- Experience with workflow orchestration tools and experiment management systems
- History working with large scale reinforcement learning
- Comfort with large scale data pipelines (Beam Spark Dask )
The expected salary range for this position is:
Annual Salary:
$315000 $560000 USD
Logistics
Education requirements: We require at least a Bachelors degree in a related field or equivalent experience.
Locationbased 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 arent 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 youre interested in this work. We think AI systems like the ones were 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.
How were different
We believe that the highestimpact AI research will be big science. At Anthropic we work as a single cohesive team on just a few largescale research efforts. And we value impact advancing our longterm 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. Were an extremely collaborative group and we host frequent research discussions to ensure that we are pursuing the highestimpact 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: GPT3 CircuitBased 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.
Required Experience:
Staff IC
Employment Type
Full-Time
