Senior ML Platform Engineer in Orlando

Our Client is seeking a senior-level software engineer with deep hands-on experience across Kubernetes infrastructure, containerized application development, cloud platforms, and production machine learning systems. This role supports a high-scale platform focused on real-time data processing, computer vision, MLOps, and cloud- deployment architectures. The ideal candidate is equally comfortable building containerized applications and operating Kubernetes infrastructure in production environments. Key Responsibilities

• Design and implement scalable machine learning training, evaluation, deployment, and monitoring pipelines.
• Build and support containerized applications deployed within Kubernetes environments.
• Deploy and optimize computer vision and machine learning models for production workloads.
• Develop Python services, APIs, and data pipelines supporting real-time systems.
• Collaborate with cross-functional teams to integrate ML models into production platforms.
• Troubleshoot and optimize cloud infrastructure, Kubernetes workloads, and production pipelines.
• Build reusable tools for model monitoring, evaluation, and operational excellence.

• 8-10+ years of overall software or infrastructure engineering experience.
• Hands-on Docker and container development experience, including writing Dockerfiles and building images.
• Deep Kubernetes experience including Deployments, Services, Ingress, PV/PVC, Helm, and production troubleshooting.
• Strong Python development experience.
• Production cloud infrastructure experience, preferably AWS and EKS.
• Experience supporting or deploying machine learning workloads in production environments.
• Experience building real-time or event-driven systems.
• Expertise with Linux/Ubuntu environments.
• Experience with technologies such as Kafka, Kinesis, Redis, or similar messaging platforms.
• Ability to clearly articulate personal ownership of systems and solutions built.

Skills

• Rancher experience.
• AWS services including SageMaker, S3, and DynamoDB.
• Computer vision experience with YOLO, OWL, SAM, VLM, or VLA models.
• Experience optimizing large-scale model performance.
• Java experience.
• High-visibility production systems experience.
• Security-conscious platform engineering experience.