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# Senior AI/ML Platform Engineer

- **Company:** TalentBridge
- **Location:** United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon S3, Cloud Engineering, Information Systems, Continuous Integration, Identity and Access Management, Key Management, Machine Learning, Azure Machine Learning, Data Streaming, Cloud Platform System, AI Platforms, Infrastructure Automation Frameworks, Information Technology, Deployment Automation, Machine Learning Operations, Functional Programming, Api Design, Api Gateway, Databricks
- **Published:** September 8, 2026
- **Apply:** https://www.dice.com/job-detail/99bd91be-325e-4ba9-b94f-b1ec0f86065c

## About the Role

* Bachelor's degree in Computer Science, Engineering, Information Systems, or related field (or equivalent experience).
 * Experience building, operating, or supporting production AI/ML platforms within cloud environments.
 * Hands-on experience with at least one AI/ML platform such as Databricks, AWS SageMaker, MLflow, Azure ML, or Vertex AI.
 * Strong background with CI/CD, Infrastructure as Code, environment management, secrets management, access controls, and deployment automation.
 * Experience supporting model development and deployment beyond experimentation and notebook-based workflows.
 * Solid understanding of cloud-native architecture, APIs, containers, compute, storage, and observability.
 * Experience creating reusable engineering frameworks, templates, and platform standards.
 * Proven ability to support AI/ML workloads in governed, production environments.
 * Strong troubleshooting skills across platform, deployment, performance, and integration challenges., * Deep Databricks experience including Unity Catalog, MLflow, Model Serving, Jobs/Workflows, Clusters, Permissions, and Cost Optimization.
 * AWS expertise including IAM, S3, Lambda, ECS/EKS, API Gateway, SageMaker, Bedrock, Networking, and Security.
 * Experience in highly regulated or mission-critical environments such as energy, industrial, healthcare, finance, or manufacturing.
 * Background in platform cost management and workload optimization.
 * Experience creating enablement materials for engineers and data science teams., Candidates with experience in MLOps, ModelOps, AI Platform Engineering, Machine Learning Infrastructure Engineering, or AI/ML Enablement Platforms will be particularly successful in this role.

## Description

Rather than developing one-off AI solutions, you'll build the foundational systems, automation, and governance that enable AI/ML teams to deploy and operate models at scale., * Design, build, and support enterprise AI/ML platforms across Databricks, AWS, MLflow, model registries, model serving, feature stores, and related technologies.

 * Develop reusable patterns for model development, deployment, monitoring, security, and production support.
 * Implement CI/CD pipelines, infrastructure automation, secrets management, access controls, and deployment frameworks.
 * Support batch, streaming, real-time, and API-based model deployment architectures.
 * Define engineering standards for experimentation, model promotion, observability, governance, and operational support.
 * Partner with data, security, infrastructure, and architecture teams to deliver production-ready AI/ML capabilities.
 * Build reference architectures, templates, and platform enablement resources to support enterprise adoption.