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Machine Learning Architect (AWS)

140 000 - 157 500$
Формат работы
remote (только USA)
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
Machine Learning Architect (AWS): Designing and delivering cloud-native machine learning solutions for customers on AWS with an accent on SageMaker, ML system architecture, MLOps, and DevOps automation. Focus on translating customer requirements into engineering backlogs, leading architecture discussions, troubleshooting production environments, and mentoring engineers.

Location: USA; fully remote, with current legal authorization to work in the United States required. Visa and work permit sponsorship is not available. The role may require up to 25% travel.

Base salary: $140,000–$157,500 per year, plus potential bonuses, commissions, equity, and other incentives.

Company

hirify.global is an AI-first cloud services company and AWS Premier Tier Services Partner that delivers cloud modernization, intelligent products, generative and agentic AI, data, DevOps, security, and managed services.

What you will do

  • Guide customers and engineering teams through Agile ceremonies and delivery activities.
  • Translate customer requirements into actionable engineering backlogs and delegate work across the team.
  • Lead requirements gathering, backlog refinement, architecture discussions, and technical documentation.
  • Design and apply DevOps practices including build automation, branching strategies, CI/CD, Infrastructure as Code, security, monitoring, logging, and alerting.
  • Troubleshoot customer development, test, and production environments and automate testing across multiple levels.
  • Write production-quality code with unit and integration tests while coaching and mentoring engineers.

Requirements

  • Deep expertise in machine learning system design and customer-facing technical consulting.
  • Experience with Infrastructure as Code tools including CloudFormation, CDK, and Terraform.
  • Expert-level experience with Amazon SageMaker and ML libraries including TensorFlow, MXNet, PyTorch, and Scikit-learn.
  • Strong understanding of feature engineering, hyperparameter tuning, and optimization strategies.
  • Familiarity with MLOps tools such as MLflow, Neptune, and Comet.
  • Ability to communicate complex technical concepts clearly, align stakeholders, and identify gaps in customer requirements.

Culture & Benefits

  • Fully remote work with a global workforce across Canada, the United States, and Latin America.
  • Medical, dental, vision, disability, and life insurance coverage.
  • 401(k) plan with company match up to 4% and immediate vesting.
  • Competitive phantom equity, flexible spending account, and equipment and office stipend.
  • Company-issued laptop, annual learning and development stipend, unlimited paid time off, and 10 paid holidays.

Hiring process

  • This is not an active opening; applications are used to build a talent pipeline for potential future opportunities.
  • Recruiters may contact aligned candidates to learn more about their background and explore future fit.

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