Acceler8 Talent
MLOps Engineer (San Francisco Bay Area)
Acceler8 Talent, San Francisco, California, United States, 94110
Senior ML Infrastructure / MLOps Engineer
Location:
SF Bay Area (On-site)
Were representing an ambitious AI research organization building physical autonomy systems powered by large-scale ML. Youll own the infrastructure that makes cutting-edge model development reliable, reproducible, and scalable
from training to deployment.
The Opportunity Be a core part of the team responsible for the machine learning foundation of a next-generation AI platform. You will help build and maintain the systems that enable performant model training, experimentation, and production workflows at scale.
What Youll Do Build and maintain scalable ML infrastructure supporting training, fine-tuning, RLHF/DPO workflows, and distributed experiments. Develop and manage data pipelines, dataset versioning, experiment tracking, and reproducible evaluation frameworks. Operate containerized training and inference environments, including CI/CD automation for models. Partner with researchers, engineers, and systems teams to enable rapid iteration and robust deployments.
What You Bring Strong experience with ML infrastructure, distributed training systems, and production-grade MLOps practices. Familiarity with containerization, orchestration, and reproducible ML workflows. Hands-on in experiment management, dataset governance, and automation tooling. A pragmatic mindset and ability to work across research and engineering functions.
Why This Role Excites People Directly shape the backbone of ML systems that support real, high-impact AI research and autonomous behavior. Work with a tight-knit, world-class team tackling foundational problems at the intersection of ML, systems, and autonomy. Competitive salary, meaningful equity, and a strong benefits package.
SF Bay Area (On-site)
Were representing an ambitious AI research organization building physical autonomy systems powered by large-scale ML. Youll own the infrastructure that makes cutting-edge model development reliable, reproducible, and scalable
from training to deployment.
The Opportunity Be a core part of the team responsible for the machine learning foundation of a next-generation AI platform. You will help build and maintain the systems that enable performant model training, experimentation, and production workflows at scale.
What Youll Do Build and maintain scalable ML infrastructure supporting training, fine-tuning, RLHF/DPO workflows, and distributed experiments. Develop and manage data pipelines, dataset versioning, experiment tracking, and reproducible evaluation frameworks. Operate containerized training and inference environments, including CI/CD automation for models. Partner with researchers, engineers, and systems teams to enable rapid iteration and robust deployments.
What You Bring Strong experience with ML infrastructure, distributed training systems, and production-grade MLOps practices. Familiarity with containerization, orchestration, and reproducible ML workflows. Hands-on in experiment management, dataset governance, and automation tooling. A pragmatic mindset and ability to work across research and engineering functions.
Why This Role Excites People Directly shape the backbone of ML systems that support real, high-impact AI research and autonomous behavior. Work with a tight-knit, world-class team tackling foundational problems at the intersection of ML, systems, and autonomy. Competitive salary, meaningful equity, and a strong benefits package.