2 дня назад
Lead AI Engineer
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
Lead AI Engineer (Machine Learning/MLOps): Design, deploy, and scale production machine learning systems, data pipelines, feature engineering infrastructure, and model training workflows with an accent on maintainability, reproducibility, and production performance. Focus on leading technical practices, integrating ML systems into applications, diagnosing model failures, and addressing scalability, latency, and resource constraints.
Location: United States · Remote
Permanent employment. This posting is for future opportunities and adds successful applicants to a candidate network for relevant roles.
Company
is an executive search firm specializing in leaders who help organizations navigate AI transformation.
What you will do
- Design, develop, deploy, and monitor machine learning models and systems that solve business problems.
- Build and optimize data pipelines, feature engineering infrastructure, and model training workflows at scale.
- Partner with data scientists, product managers, and infrastructure teams to integrate ML systems into production applications.
- Own model performance and iteration cycles by diagnosing failures, running experiments, and using production metrics.
- Lead code reviews, document technical decisions, and establish maintainable and reproducible engineering practices.
- Drive adoption of MLOps tooling, model versioning, deployment automation, and scalable ML architecture.
Requirements
- 5–8 years of production ML engineering experience, including shipping and maintaining models in live systems.
- Strong proficiency in Python and common ML frameworks, including PyTorch, TensorFlow, and scikit-learn.
- Experience with data processing tools, SQL, testing, version control, and deployment pipelines.
- Experience building and scaling data pipelines, feature stores, or model-serving infrastructure.
- Familiarity with MLOps practices and tooling.
- Strong cross-functional collaboration and communication skills, with the ability to explain technical decisions and tradeoffs to technical and non-technical audiences.
Culture & Benefits
- Remote work from the United States.
- Opportunity to be considered for future AI transformation leadership roles.
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