Senior AI/ML Platform Engineer

Machine Learning Technologies, LLC; Linthicum (MD); On-site; USD 170,000 - 230,000; Full time

Job summary

Machine Learning Technologies, LLC is seeking a Senior AI/ML Platform Engineer to design, implement, and operate a shared enterprise AI/ML platform. You will focus on platform automation, MLOps, CI/CD, cloud infrastructure, observability, reliability engineering, and cost optimization.

Responsibilities include building CI/CD pipelines, Terraform/Ansible automation, Kubernetes management, and maintaining model lifecycle components such as tracking, registries, and drift monitoring.

Qualifications

• 10+ years in platform engineering/MLOps or data/software engineering with 2+ years in production ML systems
• Bachelor's degree in Computer Science, Information Systems, Engineering, Business, or related technical discipline; Master’s preferred
• Strong Python production-grade software development is required
• Experience designing and improving ML CI/CD pipelines, automation frameworks, and deployment processes
• Hands-on experience with AWS, Azure, or GCP, including cloud resource management and cost optimization
• Advanced Kubernetes experience (cluster management, quotas, autoscaling, scheduling) and strong observability knowledge
• Production experience with Terraform and Ansible
• Solid understanding of ML lifecycle: experiment tracking, model registries, feature stores, model serving, drift monitoring
• Experience with automated model validation, testing, A/B testing, canary deployments, rollbacks and production releases
• Experience developing internal SDKs, CLI tools, reusable templates, APIs, and standardized deployment workflows
• Strong troubleshooting, incident response, root-cause analysis, and technical documentation skills

Responsibilities

• Design, implement, operate, and continuously improve the shared enterprise AI/ML platform
• Automate platform operations, CI/CD, and deployment workflows
• Manage cloud infrastructure and cost optimization
• Enhance observability and reliability engineering for the platform
• Lead internal tooling (SDKs/CLI) and developer experience
• Collaborate across teams on platform APIs and GitOps practices

Skills

Python

MLOps

Kubernetes

CI/CD

Cloud platforms

Observability

Terraform

Ansible

Model lifecycle

Experiment tracking

A/B testing

Automation

SDKs/CLI

Education

Bachelor's degree in CS/IS/Engineering/Business

Master's degree preferred

Tools

Prometheus

Grafana

Datadog

OpenTelemetry

Job description

Job Description: Position Overview: The Senior AI/ML Platform Engineer will design, implement, operate, and continuously improve the shared enterprise AI/ML platform. Key areas of focus include platform automation, MLOps, CI/CD, cloud infrastructure, observability, reliability engineering, and cost optimization.

Key Requirements:

• 10+ years of experience in platform engineering, MLOps, or data/software engineering, including 2+ years with production ML systems.
• Bachelor's degree in Computer Science, Information Systems, Engineering, Business, or a related technical discipline (Master's degree preferred).
• Strong proficiency in Python and production-grade software development.
• Experience designing and improving ML CI/CD pipelines, automation frameworks, and deployment processes.
• Hands-on experience with AWS, Azure, or GCP, including cloud resource management and cost optimization.
• Advanced Kubernetes experience (cluster management, resource quotas, autoscaling, workload scheduling).
• Experience with observability tools such as Prometheus, Grafana, Datadog, or OpenTelemetry.
• Production-scale experience with Terraform and Ansible.
• Strong understanding of the ML lifecycle, experiment tracking, model registries, feature stores, model serving, and drift monitoring.
• Experience with automated model validation, testing, A/B testing, canary deployments, rollbacks, and production releases.
• Experience developing internal SDKs, CLI tools, reusable templates, APIs, and standardized deployment workflows.
• Strong troubleshooting, incident response, root-cause analysis, and technical documentation skills.

Preferred Qualifications:

• Experience with shared platforms or Internal Developer Platforms (IDPs).
• Familiarity with LLM serving technologies (e.g., vLLM, TGI, managed LLM APIs).
• Background in government, regulated, or FedRAMP-compliant environments.
• Knowledge of the NIST AI Risk Management Framework and responsible AI governance.
• Familiarity with FinOps practices and tools (e.g., Infracost, AWS Cost Explorer).
• Expertise in GitOps, platform APIs, developer tooling, and infrastructure observability.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.