ML Platform / Infrastructure Engineer (MLOps)

ML Platform / Infrastructure Engineer (MLOps) | 3x openings | open until filled

Onsite Mon-Fri Pembroke Pines, FL

Base Salary: Senior-Level Candidates: $215,000 ~ $270,000 | Director-Level Candidates: Up to $300,000 | The final salary or hourly wage, as applicable, paid to each candidate/applicant for this position is ultimately dependent on a variety of factors, including, but not limited to, the candidate’s/applicant’s qualifications, skills, and level of experience as well as the geographical location of the position.

U.S. Citizens and Green Card Holders Only | Applicants must be legally authorized to work in the United States. Sponsorship not available.

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We're partnered with a rapidly growing organization that is expanding its AI and machine learning capabilities and is seeking multiple ML Platform / Infrastructure Engineers (MLOps) to help build and scale the infrastructure powering next-generation AI initiatives.

This is an opportunity to work at the intersection of machine learning, cloud infrastructure, and software engineering, enabling large-scale model training, deployment, monitoring, and operational excellence.

What You'll Do

• Design, build, and maintain infrastructure supporting ML model training, evaluation, deployment, and monitoring
• Develop scalable MLOps pipelines to streamline model development and release processes
• Deploy and operate machine learning services in production environments
• Improve experiment reproducibility, CI/CD processes, and model lifecycle management
• Monitor platform health, system performance, and model observability
• Optimize infrastructure for reliability, scalability, and cost efficiency
• Partner closely with research and engineering teams to support AI innovation

Required Skills & Experience

• Strong Python development and software engineering background
• Deep AWS and cloud-native architecture experience
• Hands-on expertise with Kubernetes and containerized environments
• Experience building and supporting MLOps platforms and ML deployment pipelines
• Familiarity with distributed training infrastructure
• Experience with observability and experiment-tracking tools such as MLflow, Weights & Biases, Prometheus, and Grafana
• Experience with CI/CD, Infrastructure as Code (IaC), and automation

Preferred Qualifications

• Experience supporting large-scale LLM or VLM training environments
• Knowledge of GPU clusters and distributed training frameworks
• Experience with model serving and inference optimization
• Familiarity with orchestration platforms such as Argo, Airflow, or Kubeflow

Why Join?

• High-impact role supporting cutting-edge AI initiatives
• Significant investment in expanding internal machine learning capabilities
• Opportunity to work alongside experienced engineering and leadership teams
• Competitive compensation package with relocation assistance available
• Multiple openings available

If you're passionate about building the infrastructure that enables large-scale AI and machine learning systems to thrive, we'd love to connect.

#MLOps #MachineLearning #AIInfrastructure #Kubernetes #AWS #Python #LLM #CloudEngineering #InfrastructureEngineering #Hiring #ArtificialIntelligence #MLPlatformEngineering

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Why Hays?

You will be working with a professional recruiter who has intimate knowledge of the industry and market trends. Your Hays recruiter will lead you through a thorough screening process in order to understand your skills, experience, needs, and drivers. You will also get support on resume writing, interview tips, and career planning, so when there’s a position you really want, you’re fully prepared to get it.

Nervous about an upcoming interview? Unsure how to write a new resume?

Visit the Hays Career Advice section to learn top tips to help you stand out from the crowd when job hunting.

Hays is committed to building a thriving culture of diversity that embraces people with different backgrounds, perspectives, and experiences. We believe that the more inclusive we are, the better we serve our candidates, clients, and employees. We are an equal employment opportunity employer, and we comply with all applicable laws prohibiting discrimination based on race, color, creed, sex (including pregnancy, sexual orientation, or gender identity), age, national origin or ancestry, physical or mental disability, veteran status, marital status, genetic information, HIV-positive status, as well as any other characteristic protected by federal, state, or local law. One of Hays’ guiding principles is ‘do the right thing’. We also believe that actions speak louder than words. In that regard, we train our staff on ensuring inclusivity throughout the entire recruitment process and counsel our clients on these principles. If you have any questions about Hays or any of our processes, please contact us.

In accordance with applicable federal, state, and local law protecting qualified individuals with known disabilities, Hays will attempt to reasonably accommodate those individuals unless doing so would create an undue hardship on the company. Any qualified applicant or consultant with a disability who requires an accommodation in order to perform the essential functions of the job should call or text 813.336.5570.

Drug testing may be required.