MLOps Engineer

Position Overview I'm partnering with a rapidly growing AI infrastructure company building and operating large-scale GPU environments that support AI training, fine-tuning, and inference workloads. This is an opportunity to own the orchestration and operational layer of next-generation AI infrastructure. You'll work at the intersection of ML pipelines, open-source model deployment, and GPU cluster operations, helping ensure AI workloads run efficiently and reliably at scale. Working closely with AI engineers, infrastructure teams, and enterprise customers, you'll play a key role in turning cutting-edge models into production-ready AI services. Key Responsibilities Manage and optimize GPU workloads across Kubernetes, SLURM, and Ray environments.Build, maintain, and improve ML pipelines using platforms such as Kubeflow, Airflow, or similar orchestration tools.Deploy and operationalize open-source foundation models in production GPU environments.Automate cluster provisioning, resource allocation, capacity management, and workload scheduling across GPU infrastructure.Partner with engineering teams and enterprise customers to support model deployments, pipeline operations, and infrastructure utilization.Qualifications Required 5+ years of experience in infrastructure, DevOps, ML engineering, or related technical roles.2+ years of hands-on experience supporting GPU infrastructure or AI platforms.Experience with Kubernetes, SLURM, and Ray for workload orchestration and cluster management.Hands-on experience building and managing ML pipelines using Kubeflow, Airflow, or similar tools.Experience deploying and supporting open-source foundation models such as Llama, Qwen, DeepSeek, or similar models in production environments.Experience managing cluster capacity, automation, and resource utilization across GPU infrastructure.Proficiency with Python and scripting for automation, tooling, and pipeline development.Experience working directly with customers, stakeholders, or cross-functional engineering teams.Background in an AI-native company, GPU cloud provider, AI infrastructure company, or similar environment.Nice to Have Experience with inference optimization frameworks such as vLLM, TensorRT-LLM, or TGI.Familiarity with MLflow or similar experiment tracking and model registry platforms.Exposure to InfiniBand or RoCEv2 networking in distributed training environments.Experience with observability platforms such as Prometheus, Grafana, DCGM, or similar tools.Familiarity with NVIDIA technologies including NCCL, CUDA, and distributed training frameworks.Benefits $185,000 to $225,000 base salaryAnnual performance bonusRestricted Stock Units (RSUs)This opportunity is ideal for an engineer who enjoys working at the intersection of AI infrastructure, machine learning operations, and large-scale GPU environments. You'll have the opportunity to solve complex orchestration challenges, work with cutting-edge AI models, and play a critical role in helping organizations deploy and scale next-generation AI applications. Email Your Resume In Word To AJ.Divecha@cybercoders.com Looking forward to receiving your resume through our website and going over the position with you. Clicking apply is the best way to apply. Please do NOT change the email subject line in any way. You must keep the JobID: linkedin : AD9-1995128L443 -- in the email subject line for your application to be considered. AJ Divecha - Executive Recruiter For this position, you must be currently authorized to work in the United States without the need for sponsorship for a non-immigrant visa. This is a new role. CyberCoders will consider for Employment in the City of Los Angeles qualified Applicants with Criminal Histories in a manner consistent with the requirements of the Los Angeles Fair Chance Initiative for Hiring (Ban the Box) Ordinance. This job was first posted by CyberCoders on 08/18/2026 and applications will be accepted on an ongoing basis until the position is filled or closed. Everforth CyberCoders is proud to be an Equal Opportunity Employer All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, sexual orientation, gender identity or expression, national origin, ancestry, citizenship, genetic information, registered domestic partner status, marital status, status as a crime victim, disability, protected veteran status, or any other characteristic protected by law. Our hiring process includes AI screening for keywords and minimum qualifications, and a virtual recruiter as part of the application process. 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