4 дня назад
AI Platform Engineer, Staff
172 500 - 255 875$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
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
develops 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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