обновлено 18 часов назад
Machine Learning Engineer (MLOps)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Machine Learning Engineer (MLOps) (Cybersecurity): Designing, building, and scaling production machine learning systems for real-time cyber threat detection with an accent on end-to-end ML pipelines, model serving, and production monitoring. Focus on architecting high-throughput inference infrastructure, optimizing latency and compute costs, and ensuring reliable model performance at scale.
Location: Cordoba, Argentina
Company
provides human- and agent-centric cybersecurity solutions that protect email, cloud, collaboration tools, data, and AI workflows from threats and data loss.
What you will do
- Design and build scalable ML pipelines and data infrastructure for high-throughput cyber threat detection.
- Own end-to-end deployment, monitoring, A/B testing, and performance optimization of production ML models.
- Architect model-serving solutions using REST APIs, batch prediction, and streaming to meet latency and throughput requirements.
- Build feature pipelines and infrastructure for model training and inference at scale.
- Collaborate with data scientists, data engineers, ML platform specialists, security analysts, and product managers.
- Implement monitoring, logging, and alerting to detect model degradation and production failures.
Requirements
- 3–4 years of software engineering and ML systems experience.
- Strong Python, computer science fundamentals, data structures, algorithms, and system design skills.
- Experience building end-to-end ML systems, including data pipelines, feature engineering, model training, serving, and monitoring.
- Production experience with PyTorch, TensorFlow, or Scikit-learn.
- Familiarity with MLflow, TensorFlow Serving, KServe, or similar deployment and serving frameworks.
- Experience with AWS services such as EC2, S3, SageMaker, Lambda, and RDS, plus testing, CI/CD, code review, and version control.
Nice to have
- Familiarity with Go.
- Understanding of adversarial ML, cybersecurity challenges, and security analytics.
- Experience with NLP.
Culture & Benefits
- Competitive compensation and comprehensive benefits.
- Flexible work environment.
- Annual wellness and community outreach days.
- Recognition for contributions and career development support.
- Global collaboration and networking opportunities.
Hiring process
- Submit an application with supporting information.
- Accommodation is available during the application or interview process upon request.
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