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3 дня назад

Senior Software Engineer (AI)

220 000 - 340 000$
Формат работы
onsite
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR
Senior Software Engineer (AI): Building and scaling backend services, APIs, data pipelines, and AWS infrastructure for an AI detection platform with an accent on reliability, performance, and horizontal scalability. Focus on designing high-availability systems, deploying machine learning models in production, and solving complex bottlenecks across the stack.

Location: On-site in Brooklyn, New York

Salary: $220K–$340K plus equity

Company

Develops AI detection systems, publishes research on AI detection techniques, and builds products that bring the technology into everyday use.

What you will do

  • Design and implement scalable backend services and RESTful APIs for AI detection capabilities.
  • Own the reliability, performance, observability, and incident response of production systems.
  • Architect data pipelines, caching layers, and service infrastructure on AWS.
  • Collaborate with machine learning engineers to deploy and serve models in production.
  • Identify and resolve performance and scalability bottlenecks as traffic and system complexity grow.
  • Improve engineering practices around testing, deployment, and production operations.

Requirements

  • 5+ years of professional software engineering experience with a strong backend focus.
  • Proficiency in Python and Django or comparable Python web frameworks.
  • Deep understanding of backend architecture, relational databases, message queues, caching, and asynchronous task processing.
  • Hands-on experience with AWS services including EC2, ECS/EKS, RDS, S3, SQS, CloudFront, or Lambda.
  • Experience designing highly available, horizontally scalable systems with graceful degradation.
  • Strong production debugging and performance-profiling skills.

Nice to have

  • Experience with Docker and Kubernetes.
  • Familiarity with CI/CD and infrastructure-as-code tools such as Terraform or CloudFormation.
  • Experience with monitoring and observability tools such as Datadog, Prometheus, Grafana, or ELK.
  • Experience deploying and serving deep learning models in production, including model serving, GPU infrastructure, and batch versus real-time inference.
  • Familiarity with React or frontend technologies for cross-stack collaboration.

Culture & Benefits

  • High-autonomy role with ownership of backend infrastructure and architectural decisions.
  • Mission-driven work focused on protecting authenticity through AI detection technology.
  • Close collaboration with frontend and machine learning engineering teams.
  • Equity included in the compensation package.

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