4 дня назад
AI Engineer
66 379 - 145 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
AI Engineer (Machine Learning/MLOps): Building and deploying production AI-powered data products for student retention and academic outcomes with an accent on model design, evaluation, scalable infrastructure, and measurable outputs. Focus on designing robust ML pipelines, monitoring model drift, integrating AI into education products, and translating business needs into actionable solutions.
Location: US Nationwide — Remote; home-based position
Salary: $66,379.50–$145,000 per year, plus potential bonus
Company
provides education-focused products and services that use actionable data to support schools, school services teams, student retention, and academic outcomes.
What you will do
- Develop, evaluate, deploy, and maintain AI-powered data products based on machine learning over large datasets.
- Create models, APIs, data pipelines, and production AI resources using standardized engineering practices.
- Collaborate with Product, Engineering, IT managers, data stewards, and data engineers to build secure, private, scalable AI workflows.
- Translate business needs into practical AI solutions that support product direction and measurable decisions.
- Monitor model performance, document and reproduce outputs, and implement continuous improvement and retraining.
- Identify opportunities to apply AI across business units to improve student success and academic outcomes.
Requirements
- Bachelor’s degree in Computer Science, Math, Physics, Engineering, or a related quantitative field, plus six years of related experience, or an equivalent combination.
- Hands-on experience with modern machine learning libraries, including Python-based frameworks such as TensorFlow, PyTorch, or scikit-learn, and knowledge of statistical principles.
- Proficiency with AWS, Azure, Docker, Kubernetes, and Terraform.
- Experience designing and maintaining ML pipelines with version control, containerization, and CI/CD.
- Strong analytical, planning, communication, accuracy, and problem-solving skills, with the ability to manage multiple projects independently and collaboratively.
- Ability to pass the required background check.
Nice to have
- Master’s or doctorate degree.
- Experience with MLOps frameworks such as MLflow or Kubeflow.
- Experience with NLP, recommender systems, deep learning, or other advanced ML techniques.
Culture & Benefits
- Home-based remote work within the United States.
- Benefits for eligible employees may include health benefits, retirement contributions, and paid time off.
- Equal opportunity workplace with reasonable accommodations available during the application process.
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