Real-Time ML Engineer for Production Optimization

Speria; Dunwoody (GA); On-site; USD 120,000 - 180,000; Full time

Job summary

Speria MTech in Atlanta seeks a highly skilled Machine Learning Engineer to design, build, and deploy scalable ML and optimization systems that drive real-time decision making across production workflows.

The role spans data processing, feature engineering, model development, and production deployment, with emphasis on Python, Spark, Databricks, and CI/CD. Collaboration with data engineering and a service-minded approach are essential.

Qualifications

• Bachelor's or Master's in a relevant field; MS may qualify with 1–2 years; BS typically 4–6 years
• 2–4 years experience in Machine Learning or optimization
• Experience deploying ML systems in production
• Familiarity with ML flow, Databricks, CI/CD
• Strong Python programming (production-level)
• Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn)

Responsibilities

• Design and build machine learning and optimization pipelines
• Develop and deploy production-grade models
• Build feature pipelines using distributed systems (e.g., Spark)
• Collaborate with data engineering on data readiness
• Develop decisioning systems for automated actions
• Monitor model performance and improve continuously

Skills

Machine learning

Optimization

Python programming

Production deployment

Team collaboration

Education

Bachelor’s or Master’s degree in a relevant field

Tools

Databricks

Apache Spark

CI/CD

Job description

Speria MTech in Atlanta seeks a highly skilled Machine Learning Engineer to design, build, and deploy scalable ML and optimization systems that drive real-time decision making across production workflows.

The role spans data processing, feature engineering, model development, and production deployment, with emphasis on Python, Spark, Databricks, and CI/CD. Collaboration with data engineering and a service-minded approach are essential.