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 is seeking an experienced Engineering Manager to lead our Data Infrastructure team. In this role, you'll guide a team responsible for designing, building, and maintaining the data infrastructure that powers our AI research and products. Your work will be crucial in ensuring Anthropic can continue to reliably and safely train frontier models while maintaining the highest standards of data quality and accessibility.
The Data Infrastructure team is responsible for building and operating the systems that enable us to process, store, and serve massive datasets efficiently and reliably. You'll work closely with research teams to understand their data requirements, deliver efficient and reliable data solutions, and continuously improve our data infrastructure.
Responsibilities:
- Lead and grow a team of data infrastructure engineers, providing technical guidance, career development, and performance management
- Partner with research and engineering teams to understand data requirements and architect solutions that meet their needs
- Set technical strategy and oversee development of high-scale, reliable data infrastructure systems
- Design and implement data governance best practices across the organization
- Drive improvements in our data pipeline efficiency, reliability, and maintainability
- Establish processes for effective team operations and continuous improvement
- Mentor top technical talent and help build a strong engineering culture
- Partner with recruiting to build out a world-class data infrastructure team
You may be a good fit if you:
- Have 5+ years of engineering experience, with 3+ years of engineering management experience
- Have deep expertise in building and scaling data infrastructure, including experience with technologies like Airflow, dbt, data warehouses (BigQuery, Snowflake, Databricks), and cloud services (GCP/AWS)
- Are passionate about developing engineers and building inclusive, high-performing teams
- Have excellent communication skills and can build consensus across diverse stakeholders
- Have experience setting technical strategy and roadmaps for complex infrastructure systems
- Are comfortable operating in ambiguous, fast-paced environments
- Have a track record of delivering reliable systems at scale
- Care deeply about data quality, reliability, and security
Strong candidates may also:
- Have experience working with ML infrastructure and large-scale AI training systems
- Have expertise in distributed systems and cloud architecture
- Bring experience with real-time data processing systems and streaming architectures
- Have experience managing teams during periods of rapid growth
- Have knowledge of data privacy and security best practices
- Demonstrate experience implementing data governance frameworks
- Show familiarity with modern ML development workflows and requirements
Deadline to apply: None. Applications will be reviewed on a rolling basis.
The expected salary range for this position is:
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.
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.
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