Data Science or ML Engineering

About This Role

As an MLOps Engineer at StarX Technologies, you will bridge the gap between data science and production systems. You’ll be responsible for building robust ML pipelines, enabling continuous integration and delivery for AI/ML models, and ensuring high availability in production environments.

Key Responsibilities

• Design and implement CI/CD pipelines for machine learning models

• Automate model training, deployment, and monitoring workflows

• Collaborate with data scientists to productionize models

• Ensure compliance, governance, and ethical AI practices

• Monitor and optimize model performance in real-time

Requirements

• 5+ years in Data Science or ML engineering

• Experience with tools like MLflow, Kubeflow, SageMaker, Azure AutoML, GCP Vertex AI

• Proficiency in Python language and containerization (Docker, Kubernetes) concepts

• Knowledge of model training, scoring, monitoring and drift detection techniques

• Bachelor’s or higher in Computer Science, Data Science, or similar field

Preferred Qualifications

• Experience with generative AI deployment

• Familiarity with monitoring platforms (Prometheus, Grafana)

• Certifications in cloud ML services (AWS, Azure, GCP)

• Background in regulated industries (finance, healthcare)

What We Offer