Senior AI/ML Platform Engineer

Employee Relations Associates, Inc.; Denver (CO); Hybrid; USD 170,000 - 210,000; Full time

Benefits offered by this job

Medical coverage

Dental coverage

Vision coverage

Life insurance

Short-term disability

401(k)

Holiday pay

Job summary

Employee Relations Associates, Inc. is seeking a Senior AI/ML Platform Engineer to design and scale enterprise AI/ML platforms, delivering secure, observable, and scalable infrastructure across cloud and data platforms.

You will build foundational systems, automation, and governance to enable AI/ML teams to deploy models at scale, partnering with data, security, and infrastructure teams to deliver production-ready capabilities.

Qualifications

• Bachelor's degree in CS/Engineering or related field.
• Experience building/operating production AI/ML platforms in cloud.
• Hands-on with Databricks, AWS SageMaker, MLflow, Azure ML, or Vertex AI.
• Strong CI/CD and IaC, secrets management, access controls, deployment automation.
• Experience moving beyond notebooks into production model deployment.
• Solid cloud-native architecture, APIs, containers, storage, observability.
• Experience creating reusable engineering frameworks and platform standards.
• Ability to support governed, production AI/ML workloads.
• Strong troubleshooting across platform, deployment, performance, and integration.

Responsibilities

• Design, build, and support enterprise AI/ML platforms across Databricks, AWS, MLflow, and related tech.
• Develop reusable patterns for model development, deployment, monitoring, security, and production support.
• Implement CI/CD pipelines, automation, secrets mgmt, access controls, and deployment frameworks.
• Support batch, streaming, real-time, and API-based model deployment architectures.
• Define standards for experimentation, model promotion, observability, governance, and ops support.
• Collaborate with data, security, infrastructure, and architecture teams to deliver production-ready capabilities.
• Build reference architectures, templates, and platform enablement resources for enterprise adoption.

Skills

CI/CD

Infrastructure as Code

Secrets management

Access controls

Deployment automation

Observability

Education

Bachelor's degree in Computer Science, Engineering, Information Systems, or related field

Tools

Databricks

AWS SageMaker

MLflow

Azure ML

Vertex AI

Job description

We're seeking a Senior AI/ML Platform Engineer to build and scale enterprise AI/ML platforms that support production-grade machine learning and generative AI workloads. This is a hands-on engineering role focused on creating secure, reliable, observable, and scalable AI/ML infrastructure across cloud and data platforms.

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.

Key Responsibilities

• 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.

Required Qualifications

• 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.

Preferred Qualifications

• 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.

Ideal Background

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.

TalentBridge employees are eligible for many benefit offerings such as medical, dental, vision, life insurance, short term disability, 401(k) and holiday pay!