ML Engineer - MLOps/Infrastructure Focus

INSPYR Solutions; Cupertino (CA); On-site; USD 88,166 - 106,075; Full time

Job summary

A technology solutions firm is seeking a skilled ML Engineer with MLOps and infrastructure focus. Responsibilities include designing and developing Big Data analytical applications, supporting data workflows, and implementing ML infrastructure for large language models. Candidates should have strong Python skills and hands-on experience with Machine Learning systems, AWS services, and Kubernetes. This role offers opportunities to work on robust systems while collaborating with cross-functional teams in a dynamic environment.

Qualifications

• 5+ years of experience in Python with data ingestion pipelines.
• Hands-on experience with Machine Learning using LLMs.
• Experience with distributed ML frameworks, preferably Ray.
• Strong knowledge of AWS and Kubernetes.

Responsibilities

• Support data ingestion, dataset management, and model workflows.
• Design MLOps infrastructure for large language models.
• Develop and maintain scalable ML systems and pipelines.
• Deploy and monitor ML models in production.

Skills

Python

Machine Learning

Ray

AWS

Kubernetes

Tools

Apache Spark

CI/CD tools

Job description

This range is provided by INSPYR Solutions. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$64.00/hr - $77.00/hr

ML Engineer - MLOps/Infrastructure Focus

About this Featured Opportunity: We are seeking a highly skilled ML Engineer (MLOps / Platform) to join our team. In this role, you will design and develop Big Data analytical applications, with 50% dedicated to Machine Learning infrastructure and 50% focused on server-side tasks. You will work on creating robust and scalable systems, enhancing our project code base, and ensuring seamless integration pipelines to support AI/ML projects in the Services organization.

The Opportunity for You

• Support data ingestion, dataset management, model training, and inference workflows
• Design and implement MLOps infrastructure for large language models (LLMs)
• Develop and maintain scalable ML systems and pipelines
• Collaborate with cross‑functional teams to deploy and monitor ML models in production

Key Success Factors

• Expert in Python (5+ years of experience) with proven experience building and maintaining data ingestion pipelines.
• Hands‑on Machine Learning experience using LLMs and generative AI; developing ML infrastructure and pipelines.
• Must have experience with Ray (preferred) or similar distributed ML frameworks.
• Experience with AWS cloud services infrastructure and strong Kubernetes expertise.

Nice-to-Haves

• Familiarity with Apache Spark
• Proficiency in Scala or Java; experience with other Big Data processing technologies
• CI/CD experience for ML workflows
• Experience with model versioning and experiment tracking tools

About INSPYR Solutions

Technology is our focus and quality is our commitment. As a national expert in delivering flexible technology and talent solutions, we strategically align industry and technical expertise with our clients' business objectives and cultural needs. Our solutions are tailored to each client and include a wide variety of professional services, project, and talent solutions. By always striving for excellence and focusing on the human aspect of our business, we work seamlessly with our talent and clients to match the right solutions to the right opportunities. Learn more about us at inspyrsolutions.com.

Equal Employment Opportunity

INSPYR Solutions provides Equal Employment Opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics. In addition to federal law requirements, INSPYR Solutions complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities.