AI/ML Platform Engineer

Job Description:

We are seeking a highly skilled and passionate AI/ML Platform Engineer to join our team in Irving, TX. This role is focused on building and scaling ML infrastructure, enabling seamless model development, training, deployment, and monitoring across various environments. The ideal candidate will have hands-on experience in MLOps, AutoML solutions, and deploying ML models in production.

Key Responsibilities:

• Design, build, and maintain robust ML infrastructure and pipelines to support data scientists and ML engineers.
• Collaborate with cross-functional teams to deploy and manage ML models at scale in production environments.
• Integrate AutoML frameworks to accelerate model development and experimentation.
• Implement CI/CD pipelines for ML workflows, including model versioning, retraining, and rollback.
• Manage infrastructure using IaC tools (Terraform, CloudFormation) and container orchestration platforms like Kubernetes (EKS/GKE).
• Ensure scalability, security, and observability in ML systems using logging and monitoring tools.

Required Skills:

• 5+ years of experience in ML infrastructure, DevOps, or platform engineering
• Strong hands-on experience with AutoML tools such as DataRobot, H2O.ai, Vertex AI, or Amazon SageMaker Autopilot.
• Experience deploying ML models using Docker, Kubernetes, and serving frameworks like TensorFlow Serving, TorchServe, or BentoML.
• Proficiency with Python and ML libraries (Scikit-learn, TensorFlow, PyTorch).
• Familiarity with cloud platforms (AWS, Google Cloud Platform, or Azure) and MLOps pipelines (Kubeflow, MLflow, TFX).
• Experience with CI/CD tools like Jenkins, GitLab CI, or GitHub Actions.
• Good understanding of model monitoring, drift detection, and retraining strategies.

Preferred Qualifications:

• Prior experience in regulated industries (Finance, Healthcare, etc.).
• Exposure to feature store
• Understanding of data privacy and governance as it relates to ML workflows.