ML Ops Engineer

Overview

Machine Learning AI team seeking a ML Ops Engineer to drive the full lifecycle of machine learning solutions.

Key Responsibilities

• Develop and maintain ML pipelines using tools like MLflow Kubeflow or Vertex AI.
• Automate model training testing deployment and monitoring in cloud environments (e.g. GCP AWS Azure).
• Implement CI/CD workflows for model lifecycle management including versioning monitoring and retraining.
• Monitor model performance using observability tools and ensure compliance with model governance frameworks (MRM documentationexplainability)
• Collaborate with engineering teams to provision containerized environments and support model scoring via low-latency APIs
• Leverage AutoML tools (e.g. Vertex AI AutoML H2O Driverless AI) for low-code/no-code model development documentation automation and rapid deployment

Qualifications

• 10 Years of professional experience in Software Engineering & 3Years in AIML Machine Learning Model Operations.
• Strong proficiency in Java and Python SQL and ML libraries (-learn XGBoost TensorFlow PyTorch).
• Experience with cloud platforms and containerization (Docker Kubernetes).
• Familiarity with data engineering tools (e.g. Airflow Spark) and ML Ops frameworks.
• Solid understanding of software engineering principles and DevOps practices.
• Ability to communicate complex technical concepts to non-technical stakeholders.

Donato Technologies Inc. is a trusted IT staffing consulting and software development partner headquartered in Dallas Texas. We support clients across industries by understanding their unique business needs and delivering tailored technology and workforce solutions. Our focus is on connecting the right talent with the right opportunity-ensuring clients receive dependable skilled professionals and candidates receive meaningful career growth and support. We work closely with small to mid-sized organizations to provide flexible high-quality services that drive performance innovation and long-term success.