7 дней назад
MLOps Technical Manager
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
MLOps Technical Manager (Python/MLflow/AWS): Designing and delivering scalable machine learning infrastructure, pipelines, and React interfaces for predictive maintenance, fault detection, and component lifecycle optimization with an accent on end-to-end architecture, MLOps practices, and cloud-native delivery. Focus on migrating MLflow to AWS SageMaker, building batch and real-time systems, and mentoring a team of 5+ engineers.
Location: London, United Kingdom (Hybrid) or Spain (Remote)
Company
is a technology services and consulting firm founded in 2018 that delivers digital transformation, product development, software engineering, AI and data solutions, and customer experience services.
What you will do
- Own end-to-end technical delivery of machine learning systems, from backend infrastructure to frontend integration.
- Lead architecture across the ML stack, ensuring scalability, reliability, and alignment with business goals.
- Drive the migration from MLflow to AWS SageMaker while maintaining continuity and minimizing disruption.
- Define and enforce MLOps practices for model training, serving, monitoring, deployment, and CI/CD.
- Design scalable ML infrastructure for batch and real-time environments, including ETL/ELT pipelines and large-scale data processing.
- Develop React interfaces for ML insights and lead, mentor, and provide structured feedback to a team of 5+ engineers.
Requirements
- 10+ years of experience in software, data, or ML engineering.
- Proven experience as a Tech Lead managing teams of 5+ people and owning end-to-end backend and frontend delivery.
- Deep MLOps expertise and expert-level Python proficiency.
- Mandatory hands-on experience with MLflow, plus strong AWS and cloud-native architecture experience.
- Experience with React, ETL/ELT pipelines, data engineering, Docker, and scalable data systems such as Spark or Kafka.
- Strong leadership, communication, strategic thinking, empathy, and hands-on execution skills.
Nice to have
- Experience with AWS SageMaker or similar managed ML platforms.
- Experience in safety-critical or regulated industries such as aerospace or aviation.
- Familiarity with Kafka or event-driven architectures for real-time ML pipelines.
Culture & Benefits
- Opportunity to join a fast-growing organization with a multicultural community of technology experts.
- Flexible and hybrid working environment.
- Competitive compensation package.
- Medical insurance.
- Inclusive workplace with equal employment opportunities and reasonable accommodation during the recruitment process.
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