3 дня назад
Manager, AI Solutions (MLOps)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Manager, AI Solutions (MLOps): Designing, deploying, and managing ML infrastructure and platform services for model training, experimentation, and production inference at scale with an accent on team leadership, reliability, observability, and cloud cost efficiency. Focus on standardizing model versioning, experiment tracking, containerization, CI/CD, model monitoring, incident response, and compliance across production ML systems.
Location: United States, remote
Company
is a specialist executive search firm focused on leaders who help organizations navigate AI transformation.
What you will do
- Own the design, deployment, and lifecycle management of ML infrastructure and platform services supporting model training, experimentation, and production inference at scale.
- Lead and mentor MLOps and platform engineering teams, set technical direction, and remove execution blockers.
- Partner with data science, ML engineering, and software engineering teams to define SLAs, reliability standards, and tooling that accelerate model delivery.
- Standardize model versioning, experiment tracking, containerization, and CI/CD pipelines for ML development and deployment.
- Own observability, monitoring, incident response, model drift detection, data quality, and production performance practices.
- Optimize compute, storage, and cloud costs while embedding compliance, data privacy, and audit logging into platform design.
Requirements
- 6+ years of hands-on experience in MLOps, platform engineering, or ML infrastructure, including 2–3 years managing or mentoring technical teams.
- Experience building and scaling ML pipelines, Docker and Kubernetes-based containerization, Airflow, Kubeflow, or equivalent orchestration, and CI/CD systems.
- Deep familiarity with AWS, Azure, or GCP and experience designing reliable, cost-efficient cloud ML infrastructure.
- Strong software engineering practices and production-quality coding experience in Python, Go, or similar languages.
- Experience defining and monitoring SLAs, observability, logging, and incident response for ML or data-intensive production systems.
- Ability to communicate technical trade-offs to non-technical stakeholders and align infrastructure decisions with business outcomes.
Culture & Benefits
- Permanent remote opportunity based in the United States.
- Role centered on operational excellence, cross-functional collaboration, and AI transformation leadership.
- This posting is for future opportunities; applications are added to a candidate network for potential relevant roles.
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