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Engineer II - Automation & Development (Remote) (AI)
100 000 - 145 000$
Описание вакансии
Текст:
TL;DR
Engineer II - Automation & Development (Remote) (Machine Learning): Developing and deploying machine learning models for cloud cost attribution, forecasting, and anomaly detection with an accent on large-scale financial data, model evaluation, and production integration. Focus on designing experiments, building reproducible Python solutions, and monitoring model accuracy across distributed cloud usage datasets.
Location: USA - Remote; U.S. citizenship or Green Card/permanent resident status required
Salary: $100,000–$145,000 per year, plus eligibility for bonuses and equity grants
Company
Cybersecurity company building an AI-native platform that protects organizations and processes large-scale distributed security data.
What you will do
- Develop, train, and evaluate machine learning models for cloud cost attribution and resource-consumption analysis.
- Translate business requirements into modeling problems involving cost allocation, forecasting, and anomaly detection.
- Design and run experiments to validate attribution accuracy across teams, products, and business units.
- Partner with engineering teams to productionize models and monitor performance and accuracy over time.
- Analyze large-scale cloud usage and financial datasets and report project status.
Requirements
- U.S. citizenship or Green Card/permanent resident status
- Experience developing, training, and evaluating machine learning models on structured business or financial data.
- Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or scikit-learn.
- Experience with large-scale datasets, distributed data processing, statistics, probability, and experimental design.
- Knowledge of feature engineering, model evaluation, SQL, relational databases, and reproducible testing.
- Strong communication, collaboration, attention to detail, and focus on financial data accuracy.
Nice to have
- Experience with cloud billing data, FinOps, resource tagging, cost allocation, or chargeback/showback systems.
- Knowledge of MLOps, model monitoring, versioning, and CI/CD for ML.
- Exposure to Kafka, Spark Streaming, AWS, GCP, Azure, or time-series forecasting.
- Research publications or contributions to open-source ML projects.
Culture & Benefits
- Remote work with flexibility and autonomy.
- Health, physical, and mental wellness programs.
- Competitive vacation and paid holidays.
- Paid parental and adoption leave.
- Professional development opportunities, employee networks, and volunteer programs.
- Bonuses, equity grants, health insurance, 401(k), and paid time off.