TechStar Group
ML Engineer with Timeseries data experience
TechStar Group, Atlanta, Georgia, United States, 30383
ML Engineer with Timeseries data experience
Hybrid in Atlanta, GA (locals preferred)
$58/hr on C2C, Any Visa
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Responsibilities and Qualifications
Model Development: Design, build, train, and optimize ML/DL models for time-series forecasting, prediction, anomaly detection, and causal inference.
Data Pipelines: Create robust data pipelines for collection, preprocessing, feature engineering, and labeling of large-scale time-series data.
Scalable Systems: Architect and implement scalable AI/ML infrastructure and MLOps pipelines (CI/CD, monitoring) for production deployment.
Collaboration: Work with data engineers, software developers, and domain experts to integrate AI solutions.
Performance: Monitor, troubleshoot, and optimize model performance, ensuring robustness and real-world applicability.
Languages & Frameworks: Good understanding of AWS Framework, Python (Pandas, NumPy), PyTorch, TensorFlow, Scikit-learn, PySpark.
ML/DL Expertise:
Strong grasp of time-series models
(ARIMA, Prophet, Deep Learning), anomaly detection, and predictive analytics
Data Handling: Experience with large datasets, feature engineering, and scalable data processing.
Seniority level Mid-Senior level
Employment type Full-time
Job function Information Technology
Industries IT Services and IT Consulting
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$58/hr on C2C, Any Visa
Get AI-powered advice on this job and more exclusive features.
Referrals increase your chances of interviewing at TechStar Group by 2x
Get notified about new Machine Learning Engineer jobs in
Atlanta, GA .
Responsibilities and Qualifications
Model Development: Design, build, train, and optimize ML/DL models for time-series forecasting, prediction, anomaly detection, and causal inference.
Data Pipelines: Create robust data pipelines for collection, preprocessing, feature engineering, and labeling of large-scale time-series data.
Scalable Systems: Architect and implement scalable AI/ML infrastructure and MLOps pipelines (CI/CD, monitoring) for production deployment.
Collaboration: Work with data engineers, software developers, and domain experts to integrate AI solutions.
Performance: Monitor, troubleshoot, and optimize model performance, ensuring robustness and real-world applicability.
Languages & Frameworks: Good understanding of AWS Framework, Python (Pandas, NumPy), PyTorch, TensorFlow, Scikit-learn, PySpark.
ML/DL Expertise:
Strong grasp of time-series models
(ARIMA, Prophet, Deep Learning), anomaly detection, and predictive analytics
Data Handling: Experience with large datasets, feature engineering, and scalable data processing.
Seniority level Mid-Senior level
Employment type Full-time
Job function Information Technology
Industries IT Services and IT Consulting
#J-18808-Ljbffr