Machine Learning Engineer

Speria MTech offers the chance to build machine learning and optimization solutions that support real-time decision-making. This role in Atlanta, GA (hybrid) focuses on taking operational data and turning it into predictions and automated actions, with production deployment, monitoring, and continuous improvement built into the work.

What you will do

• Design and build machine learning and optimization pipelines that support decisioning in production
• Develop and deploy production-grade models for operational use
• Create feature pipelines using distributed systems such as Spark
• Collaborate with data engineering to support data readiness for modeling and deployment
• Develop decisioning systems that drive automated actions
• Monitor model performance and improve continuously after deployment

What you bring

• Bachelor’s or Master’s degree 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 machine learning systems in production
• Familiarity with an end-to-end machine learning flow, including Databricks and CI/CD
• Strong Python programming at production level
• Experience with ML frameworks including PyTorch, TensorFlow, and scikit-learn

Tools and technologies you will work with

• Python, PyTorch, TensorFlow, scikit-learn
• Spark, Databricks
• CI/CD, Git
• SQL
• LLMs, generative AI, and agent-based systems

Preferred skills

• SQL and Apache Spark experience
• Feature engineering pipelines for machine learning
• Git, CI/CD, and reproducible workflows
• Experience with real-time systems
• Familiarity with LLMs, generative AI, and agent-based systems
• MS may qualify with 1–2 years; BS typically 4–6 years

Location: Atlanta, GA (hybrid)

Minimum experience: 2 years