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Quantum Technologies LLC Logo
Senior AI/ML Platform Engineer

Quantum Technologies LLC

 

Linthicum Heights, MD, USA

Posted On: Just posted
Experience: 10+ years
Availability: Onsite
Openings: 1
Category: AI/ML Platform Engineer
Tenure: No Preference/Any
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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

Education

Any Graduate

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