PDSSOFT INC.
ML Engineer with Timeseries Data Experience
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an ML Engineer with time-series data experience in Atlanta, GA. Contract length is unspecified, offering competitive pay. Key skills include Python, AWS, PyTorch, TensorFlow, and expertise in time-series models and data pipelines.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
January 6, 2026
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Atlanta, GA
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🧠 - Skills detailed
#Datasets #Spark (Apache Spark) #Python #NumPy #Deployment #Scala #Data Processing #Data Pipeline #AWS (Amazon Web Services) #ML (Machine Learning) #PySpark #AI (Artificial Intelligence) #TensorFlow #Anomaly Detection #Deep Learning #Data Engineering #Forecasting #PyTorch #Pandas #Monitoring
Role description
ML Engineer with Timeseries data experience
Location: Atlanta, GA--Day1 onsite
Job Description
• 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.
ML Engineer with Timeseries data experience
Location: Atlanta, GA--Day1 onsite
Job Description
• 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.
