Overview
Hybrid
Depends on Experience
Full Time
Skills
Algorithms
Data Analysis
Machine Learning (ML)
Reliability Engineering
Operational Efficiency
Data Science
Streaming
Research
EDA
Dashboard
Visualization
Job Details
ML Engineer
Location : NYC , Seattle WA, Santa Clara, Bay Area , CA
Job Summary:
Looking for a skilled Machine Leaming Engineer specializing in anomaly detection to join our team. The ideal candidate will design, develop, and deploy machine learning models that identify unusual patterns or outliers in large-scale datasets to improve system reliability and operational efficiency.
Key Responsibilities:
- Design and implement robust anomaly detection algorithms using statistical, machine learning, and deep leaming techniques.
- Develop scalable data pipelines to process and analyze large volumes of streaming and batch data
- Collaborate with cross-functional teams (engineering, data science, product) to define problem statements, gather requirements, and deliver ML solutions.
- Perform exploratory data analysis (EDA) and feature engineering tailored for anomaly detection tasks.
- Train, evaluate, and optimize models to maximize detection accuracy and minimize false positive/negatives.
- Monitor model performance and update models as needed in production environments.
- Write clean, maintainable, and well-documented code following best practices.
- Stay up to date with the latest research and technologies in anomaly detection and machine leaming.
- Assist in developing dashboards and tools for anomaly visualization and alerting.
Required Qualifications:
- Bachelor s or master s degree in computer science, Data Science, Engineering, Mathematics, or a related field.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.