MLOps Engineer

Global Payments Inc.

Atlanta (GA)

On-site

USD 90,000 - 130,000

Full time

14 days+
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Job summary

A leading payment solutions company in Atlanta seeks a Technical Recruitment Specialist to support AI and ML initiatives. The role involves building and maintaining scalable systems, managing AI infrastructure, and implementing security best practices. Ideal candidates should have extensive experience in DevOps, particularly within AI/ML environments, along with strong skills in cloud-native services and CI/CD tools.

Qualifications

  • 4+ years of DevOps or AI Ops experience, preferably in AI/ML environments.
  • Hands-on experience with cloud-native services and GPU management.
  • Strong skills in CI/CD tools and configuration management.

Responsibilities

  • Design and implement CI/CD pipelines for AI and ML model training.
  • Provision and manage AI infrastructure across cloud hyperscalers.
  • Monitor and optimize performance of AI workloads.

Skills

DevOps experience
AI Operations experience
Infrastructure engineering
CI/CD tools
Scripting languages
Kubernetes knowledge

Tools

Terraform
Docker
Kubernetes
AWS/GCP

Job description

Technical Recruitment Specialist at Global Payments

At this time, we are unable to offer visa sponsorship for this position. Candidates must be legally authorized to work in the United States (or applicable country) on a full‑time basis without the need for current or future immigration sponsorship. Please note, we are not accepting candidates on H1B or OPT status

OVERVIEW

We are looking for an experienced AI Ops Engineer to support our AI and ML initiatives, including GenAI platform development, deployment automation, and infrastructure optimization. You will play a critical role in building and maintaining scalable, secure, and observable systems that power scalable RAG solutions, model training platforms, and agentic AI workflows across the enterprise.

RESPONSIBILITIES
  • Design and implement CI/CD pipelines for AI and ML model training, evaluation, and RAG system deployment (including LLMs, vectorDB, embedding and reranking models, governance and observability systems, and guardrails).
  • Provision and manage AI infrastructure across cloud hyperscalers (AWS/GCP), using infrastructure‑as‑code tools -strong preference for Terraform-.
  • Maintain containerized environments (Docker, Kubernetes) optimized for GPU workloads and distributed compute.
  • Support vector database, feature store, and embedding store deployments (e.g., pgVector, Pinecone, Redis, Featureform. MongoDB Atlas, etc).
  • Monitor and optimize performance, availability, and cost of AI workloads, using observability tools (e.g., Prometheus, Grafana, Datadog, or managed cloud offerings).
  • Collaborate with data scientists, AI/ML engineers, and other members of the platform team to ensure smooth transitions from experimentation to production.
  • Implement security best practices including secrets management, model access control, data encryption, and audit logging for AI pipelines.
  • Help support the deployment and orchestration of agentic AI systems (LangChain, LangGraph, CrewAI, Copilot Studio, AgentSpace, etc.).
Must Haves:
  • 4+ years of DevOps, AI Ops, or infrastructure engineering experience. Preferably with 2+ years in AI/ML environments.
  • Hands‑on experience with cloud‑native services (AWS Bedrock/SageMaker, GCP Vertex AI, or Azure ML) and GPU infrastructure management.
  • Strong skills in CI/CD tools (GitHub Actions, ArgoCD, Jenkins) and configuration management (Ansible, Helm, etc.).
  • Proficient in scripting languages like Python, Bash, -Go or similar is a nice plus-.
  • Experience with monitoring, logging, and alerting systems for AI/ML workloads.
  • Deep understanding of Kubernetes and container lifecycle management.
Bonus Attributes:
  • Exposure to AI Ops tooling such as MLflow, Kubeflow, SageMaker Pipelines, or Vertex Pipelines.
  • Familiarity with prompt engineering, model fine‑tuning, and inference serving.
  • Experience with secure AI deployment and compliance frameworks
  • Knowledge of model versioning, drift detection, and scalable rollback strategies.
Abilities:
  • Ability to work with a high level of initiative, accuracy, and attention to detail.
  • Ability to prioritize multiple assignments effectively. Ability to meet established deadlines.
  • Ability to successfully, efficiently, and professionally interact with staff and customers.
  • Critical thinking ability ranging from moderately to highly complex.
  • Flexibility in meeting the business needs of the customer and the company.
  • Ability to work creatively and independently with latitude and minimal supervision.
  • Ability to utilize experience and judgment in accomplishing assigned goals.
  • Experience in navigating organizational structure.
Travel Required: 2%

Travel Required: 2%

Physical Demands:
  • Standing/ Walking – minimal level
  • Sitting – moderate to high level
  • Lifting – up to 15 lbs.
  • Visual Concentration – high level
  • Work Environment – typical office environment.
Position Type and Expected Hours of Work: Full Time

Position Type and Expected Hours of Work: Full Time

Disclaimer:

The above statement is intended to describe the general nature and level of work being performed. It is not intended to be an exhaustive list of responsibilities, duties and skills required.

Global Payments Inc. is an equal opportunity employer. Global Payments provides equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex (including pregnancy), national origin, ancestry, age, marital status, sexual orientation, gender identity or expression, disability, veteran status, genetic information or any other basis protected by law. If you wish to request reasonable accommodations related to applying for employment or provide feedback about the accessibility of this website, please contact jobs@globalpay.com.

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