ML Engineer with Timeseries data experience

PDSSOFT INC.; Atlanta (GA); On-site; USD 120,000 - 180,000; Part time

Job summary

A technology company in Atlanta is seeking a skilled ML Engineer with expertise in time-series modeling and data pipelines. The role involves designing, building, and optimizing machine learning models for forecasting and anomaly detection, as well as architecting scalable infrastructure for production. Candidates should be proficient in AWS, Python, and various ML frameworks. This contract position requires on-site presence from day one.

Qualifications

• Strong grasp of time-series models like ARIMA and Prophet.
• Experience with large datasets and scalable data processing.
• Ability to create robust data pipelines and optimize model performance.

Responsibilities

• Design, build, train, and optimize ML/DL models for time-series forecasting.
• Create robust data pipelines for large-scale time-series data.
• Architect scalable AI/ML infrastructure for production deployment.
• Collaborate with data engineers, software developers, and domain experts to implement AI solutions.
• Monitor and optimize model performance for real-world use cases.

Skills

Time-series modeling expertise

AWS Framework

Python (Pandas, NumPy)

PyTorch

TensorFlow

Scikit-learn

PySpark

Tools

AWS

Python

PyTorch

TensorFlow

Scikit-learn

PySpark

Job description

ML Engineer with Timeseries data experience

Direct message the job poster from PDSSOFT INC.

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.

Seniority level

Not Applicable

Employment type

Contract

Job function

IT Services and IT Consulting, Information Services, and Technology, Information and Media