MLOps

Job Tittle : Lead ML Infra (MLOps) Engineer

Location : SFO, CA / Dallas, TX / Chicago, IL / NYC, NY

About the Role We are seeking a highly skilled Lead ML Infrastructure Engineer to spearhead the development, deployment, and scaling of machine learning infrastructure. This pivotal role involves collaborating closely with data scientists, ML engineers, and operations teams to build robust, scalable, and efficient machine learning pipelines. The ideal candidate will be passionate about pushing the boundaries of ML infrastructure, and possess a deep understanding of cloud platforms, containerization, and big data technologies.

Responsibilities

• Lead the design, implementation, and maintenance of scalable ML infrastructure solutions.
• Collaborate with data science and ML teams to optimize model deployment workflows.
• Develop and manage CI / CD pipelines to automate deployment processes.
• Architect and implement containerized environments using Docker and Kubernetes.
• Ensure infrastructure security, reliability, and compliance across cloud platforms.
• Optimize resource utilization and cost-efficiency in cloud environments.
• Drive best practices in Infrastructure as Code (IaC) with tools like Terraform.
• Stay current with the latest advancements in ML frameworks, cloud services, and infrastructure tooling.
• Mentor junior team members and promote a culture of continuous improvement.

Requirements

Preferred Qualifications : Master"s or Bachelor"s or Master"s in Computer Science, Data Science, or related field. Certifications in cloud platforms (e.g., Google Cloud Platform Professional Cloud Architect, AWS Certified Solutions Architect). Demonstrated experience leading a team or managing complex infrastructure projects. Contributions to open-source ML or DevOps projects. Experience with monitoring and logging tools such as Prometheus, Grafana, ELK stack.