Senior DevOps / MLOps Engineer

Headquartered in Silicon Valley, GenBio AI is a newly established startup where a collective of visionary scientists, engineers, and entrepreneurs are dedicated to transforming the landscape of biology and medicine through the power of Generative AI. Our team comprises leading minds and innovators in AI and biological science, pushing the boundaries of what is possible. We are committed to decoding biology holistically and enabling the next generation of life-transforming solutions. As the first mover in pan-modal Large Biological Models (LBMs), we are pioneering a new era of biomedicine. With headquarters in Silicon Valley, and branch offices in Paris and Abu Dhabi, we are poised to make a global impact. Join us as we embark on this journey to redefine the future of biology and medicine through the transformative power of Generative AI.

We are now looking for an experienced and motivated hands-on leader for a high-visibility position within our core infrastructure team. This role will lead a variety of critical tasks across DevOps, MLOps, and security/IT with cross-functional duties in multiple teams. This is a unique opportunity to shape the direction of the infrastructure which powers our models, enabling groundbreaking discoveries, and accelerating real-world applications with our partners.

• Manage and maintain infrastructure, including Kubernetes GPU resource scheduling, scaling, monitoring, logging, and performance optimization.
• Develop and maintain automated machine learning pipelines using tools such as Kubeflow and Ray.
• Manage and support collaboration and productivity platforms, including Google Workspace, GitLab, and related CI/CD integrations.
• Implement and enforce cybersecurity policies and best practices to safeguard sensitive data and systems.
• Provide technical support to team members by troubleshooting hardware, software, and network issues.

• Bachelor’s degree in Computer Science, Information Technology, or a related field.
• 3+ years of experience in Kubernetes administration and development.
• Hands-on experience in managing machine learning model lifecycles, model serving, and distributed training.
• Proven experience in automation and strong systems engineering skills.
• Solid understanding of cybersecurity principles and best practices.
• Strong sense of ownership and responsibility, with the ability to handle urgent operational issues to ensure smooth team development and deployment.

• MLOps Expertise: Proficiency in MLOps frameworks and tools, such as ModelDB, Kubeflow, Pachyderm, and Data Version Control (DVC).
• Domain Knowledge: Basic understanding of biology or chemistry; experience in the pharmaceutical or biotech industry is a plus.
• Software Engineering Background: Strong foundation in software engineering, with a transition into technical operations roles.
• Security Awareness: Ability to identify security risks and implement effective mitigation measures.
• Start-up Experience: Demonstrated experience in start-up environments, showcasing adaptability and problem-solving skills.
• Production Support: Experience supporting both production systems and machine learning pipelines.
• Educational: Master’s/Ph.D. in Computer Science, a related technical field, or equivalent practical experience.
• Leadership Skills: Proven ability to lead and develop engineering teams of 3-5 members or more.

Join us as we embark on this journey to redefine the future of biology and medicine.

We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.