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4 дня назад

AI Platform Engineer, Staff

172 500 - 255 875$
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

Текст:
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TL;DR
AI Platform Engineer, Staff (AI/ML): Building and evolving secure, scalable AI/ML platforms, cloud-native infrastructure, data pipelines, and APIs for enterprise Customer Experience products with an accent on production reliability, compliance, and large-scale data processing. Focus on architecting distributed systems, defining model-serving and monitoring standards, mentoring senior engineers, and responding to high-severity production issues.

Location: McLean, Virginia, United States

Annual base salary: $172,500–$255,875

Company

hirify.global develops hirify.global Experience Cloud, a SaaS platform for managing customer, employee, patient, resident, and candidate experiences.

What you will do

  • Set the technical direction, architecture, and engineering standards for the AI/ML platform.
  • Architect in-house and cloud-native ML infrastructure, secure data pipelines, scalable data processing, and APIs.
  • Define production standards for model and pipeline monitoring, maintenance, optimization, security, compliance, and reliability.
  • Partner with product, design, and engineering leadership to shape Customer Experience features.
  • Mentor senior engineers, lead design reviews, and drive technical decisions across multiple teams.
  • Participate in scheduled on-call rotations and respond to high-severity incidents affecting internal and customer-facing systems.

Requirements

  • BA/BS in Computer Science or a related technical discipline, or equivalent practical experience.
  • 8+ years of production software development experience with Python, Java, or Scala, including technical leadership beyond a single team.
  • Deep experience designing and operating microservices and distributed systems at scale, including Spark, Hadoop, and Kafka.
  • Experience deploying and operating services on Kubernetes, including setting standards for regulated environments.
  • Strong experience with relational SQL and Postgres.
  • Demonstrated ability to drive cross-team technical decisions and mentor senior engineers.

Nice to have

  • Experience with AWS services including EC2, S3, IAM, VPC, EKS, and SageMaker.
  • AWS Certified Machine Learning Specialty or Solutions Architect certification.
  • Experience with ML model-serving platforms such as TensorFlow Serving, TensorRT, Triton, or KServe.
  • Experience with Airflow, Kubeflow, Django, Spring, NoSQL databases, or Elasticsearch.
  • Experience defining platform strategies, technical roadmaps, or engineering standards.

Culture & Benefits

  • Medical, dental, and vision coverage.
  • 401(k), disability, life, and AD&D insurance.
  • Statutory leaves, paid parental leave, and paid holidays.
  • Equal opportunity workplace focused on diversity and inclusion.

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