Job description

Sr. ML Platform Engineer Job at a Glance • Title: Sr. ML Platform Engineer • Location: Orlando, FL (4 days onsite) • Contract: 12 months initial with potential for extension of up to 22 months or conversion to full time with the client • Pay: $75.00-$80.00/hour + optional medical, dental, vision, 401(k) match Overview 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-native 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. Required Skills • 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. Preferred 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. Why Should I Apply? Join a highly visible engineering team building cloud-native machine learning and computer vision platforms at scale. This role offers the opportunity to solve challenging infrastructure, Kubernetes, and MLOps problems while contributing to real-world systems that support millions of users and large-scale production workloads. About CEI As a trusted technology partner, CEI delivers solutions that help our customers transform their business and achieve meaningful results. From strategy and custom application development through application management - our technology and digital experience services are tailored to meet each unique need of our customers. Our staffing solutions bring specialized skills to complement our customers' workforce and project requirements. #INDGEN #ZR

Requirements

Must-haves

Sr. ML Platform Engineer
Job at a Glance
Title: Sr. ML Platform Engineer
Location: Orlando, FL (4 days onsite)
Contract: 12 months initial with potential for extension of up to 22 months or conversion to full time with the client
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.

Nice-to-haves

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.
Why Should I Apply?

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

mlkubernetesmachine learningpythondockerawsjava

Platform: bullhorn
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)