1 день назад
Lead AI/ML 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/ML Engineer (AI/ML, MLOps): Designing and deploying scalable AI/ML pipelines and production systems for complex enterprise initiatives with an accent on LLMs, Generative AI, cloud platforms, and agentic frameworks. Focus on optimizing model performance, latency, and cost, implementing MLOps and CI/CD, and leading technical architecture and engineering teams.
Location: Mexico; remote work from home with no daily office travel required
Company
provides strategic database, analytics, cloud, and AI services that support digital transformation for mid-sized and large enterprises.
What you will do
- Lead the architecture and strategic development of high-performance AI and machine learning pipelines for complex enterprise initiatives.
- Deploy, manage, fine-tune, and scale pre-trained and custom AI models, including LLMs, vision models, and Generative AI systems.
- Transform research and prototype models into resilient, production-grade systems with strong performance, latency, and cost efficiency.
- Integrate AI/ML solutions with AWS, GCP, and Azure, using Docker and Kubernetes across cloud and edge environments.
- Implement MLOps practices including model testing, CI/CD, versioning, monitoring, logging, explainability, and maintenance.
- Lead engineers, mentor team members, and align AI roadmaps with product managers, clients, executives, and cross-functional engineering teams.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, Artificial Intelligence, or a related quantitative field.
- 7–10 years of experience in machine learning engineering, software development with an ML/AI focus, or a related role.
- Expert knowledge of ADK and other agentic frameworks, with hands-on experience implementing production agents.
- Expert Python programming skills and proficiency with TensorFlow, PyTorch, or Scikit-learn.
- Extensive experience with AWS, GCP, or Azure; Docker and Kubernetes; data engineering, ETL/ELT, Git, and scalable distributed AI/ML systems.
- Strong knowledge of ML pipelines and MLOps practices, including Kubeflow, MLflow or managed cloud services, model monitoring, and AI CI/CD.
Nice to have
- Ph.D. in a relevant field.
Culture & Benefits
- Remote work from home with a stable internet connection and no daily office commute.
- Competitive total rewards package with paid vacation and sick days.
- Training allowance, professional development days, training opportunities, and certification support.
- Company-provided home-office equipment, including a laptop with a choice of operating system, plus an annual workspace budget.
- Annual wellness budget and a paid day for volunteering.
Hiring process
- Applicants must fulfill the requirements necessary to obtain a background check.
- Accommodations are available upon request during the selection process.
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