3 месяца назад
Machine Learning Infrastructure Engineer (AI)
29 167 - 41 667$
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
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TL;DR
Machine Learning Infrastructure Engineer (AI): Building and scaling the infrastructure and data pipelines for Safeguards research to detect and mitigate AI misuse with an accent on reducing iteration time for researchers. Focus on designing high-performance tooling for large-scale inference, scoring workloads, and bridging the gap between research experiments and production-grade systems.
Location: Hybrid (San Francisco, CA or New York City, NY). Staff are expected to be in the office at least 25% of the time.
Salary: $350,000 - $500,000 USD
Company
Anthropic is a public benefit corporation focused on creating reliable, interpretable, and steerable AI systems to ensure they are safe and beneficial for society.
What you will do
- Build and scale the infrastructure and data pipelines supporting Safeguards machine learning research.
- Own training, evaluation, and scoring workflows to minimize the time between research ideas and results.
- Design libraries and command-line tools that abstract complex system internals for researchers.
- Implement correctness and sanity checking within the stack to maintain result trustworthiness as models evolve.
- Transition high-value research experiments into reliable, production-grade jobs.
- Optimize the throughput, cost, and reliability of large-scale inference and scoring workloads.
Requirements
- Proficiency in Python and strong software engineering fundamentals.
- Experience building and operating production-grade data-intensive or distributed systems.
- Track record of developing infrastructure or tooling used as a dependency by other engineers/researchers.
- Ability to work across the entire research-to-deployment pipeline.
- Experience debugging performance and correctness issues across unfamiliar technical stacks.
- Must be based in or able to work from San Francisco, CA or New York City, NY.
Nice to have
- Experience with high-performance, large-scale ML systems.
- Familiarity with transformers, language modeling, and model internals.
- Knowledge of GPU/accelerator programming or inference optimization.
- Experience building experiment tracking, caching layers, or evaluation harnesses.
- Interest in AI misuse risks and mitigations.
Culture & Benefits
- Competitive compensation with optional equity donation matching.
- Generous vacation and parental leave policies.
- Flexible working hours and collaborative office environments.
- Visa sponsorship availability for qualified candidates.
- Commitment to diverse perspectives and inclusive hiring practices.
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