Production ML Engineer — Real-Time Inference & MLOps

Paroksya; United States; Hybrid; USD 120,000 - 170,000; Full time

Job summary

Paroksya is seeking a hands-on ML engineer to build production-grade models for real client products in the United States. You will design and train models for client-specific use cases and own the production inference pipeline from data to deployment, ensuring reliability under real traffic.

You'll collaborate with data engineering and stakeholders to explain model behavior, monitor performance, and iterate with low-latency inference expertise. Prior experience with ML deployment is essential.

Qualifications

• 3+ years shipping ML models to production.
• Strong Python, comfortable with PyTorch or TensorFlow.
• Understanding of MLOps: deployment and monitoring.

Responsibilities

• Design and train models for client-specific use cases.
• Build the production inference pipeline, not just the notebook.
• Work with data engineering to ensure clean, reliable training data.
• Explain model behavior and limitations clearly to non-technical stakeholders.

Skills

Python

MLOps

Production ML

PyTorch

TensorFlow

Model deployment

Tools

AWS SageMaker

Real-time inference systems

Job description

Paroksya is seeking a hands-on ML engineer to build production-grade models for real client products in the United States. You will design and train models for client-specific use cases and own the production inference pipeline from data to deployment, ensuring reliability under real traffic.

You'll collaborate with data engineering and stakeholders to explain model behavior, monitor performance, and iterate with low-latency inference expertise. Prior experience with ML deployment is essential.