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7 часов назад

Principal Generalist Engineer (ML)

Формат работы
remote (только South_africa)
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
SA
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
Principal Generalist Engineer (ML) (Distributed Systems/Infrastructure): Building reliable, scalable, and observable production systems across application services, distributed systems, infrastructure, data pipelines, and ML systems with an accent on end-to-end ownership, performance, and operational reliability. Focus on designing systems from ambiguous problems, debugging failures across multiple layers, and deploying reproducible ML pipelines with monitoring for performance, drift, and cost.

Location: Remote, South Africa

Company

hirify.global is an African financial platform providing payments, banking, credit, cross-border, and business management tools for businesses and individuals.

What you will do

  • Design and build reliable, scalable, observable production systems.
  • Own problems end to end, from requirements and system design through implementation, deployment, and operations.
  • Work across application services, distributed systems, infrastructure, data pipelines, and machine learning systems.
  • Debug complex production issues and improve performance, latency, reliability, and cost efficiency.
  • Contribute to architecture, technical direction, maintainable code, and engineering standards.
  • Train, evaluate, deploy, and monitor ML models and reproducible pipelines when ML is the appropriate solution.

Requirements

  • Strong computer science fundamentals, including data structures and algorithms, operating systems, networking, and distributed systems.
  • Solid probability and statistics knowledge.
  • Experience building production systems at scale and understanding system behavior under load and failure.
  • Ability to work across Go, Java, Python, Rust, and SQL.
  • Comfort with Linux, containers, Kubernetes, data systems, streaming systems, and ML infrastructure.
  • Strong debugging skills and the ability to reason using invariants and failure modes.

Culture & Benefits

  • People-first environment focused on well-being, respect, inclusion, and open communication.
  • Learning and development support, knowledge sharing, training, and internal technical talks.
  • Salary, pension, health insurance, paid leave, and other benefits.

Hiring process

  • Initial recruiter conversation about background, goals, and the role.
  • Take-home technical assessment followed by a discussion.
  • System design interview and final technical and behavioural interview with an executive team member.

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