In this dynamic and innovative environment, you'll lead a team of 2-3 members in our 3 offices as a start, collaborating with engineers, scientists, and machine learning researchers to develop a platform that enhances productivity organization-wide. Your role includes establishing standards and shaping the developer experience throughout the company.As we are in the early stages of our journey, with ongoing learning and some ambiguity, your prior experience and proactive approach will be essential in defining your impact in this newly established position.
Responsibilities
You will continue to develop and empower a diverse team of developers, providing technical guidance and direction and anticipating future resource needs in line with business goals and priorities
Develop and implement a scalable technical strategy to address complex challenges
Establish technical standards and enhance the developer experience across the organization
Define team goals, drive execution, and manage cloud infrastructure (GCP, Docker, Terraform, etc.)
Develop reliability and observability strategies to ensure system performance and resilience
Build tools and processes for effective operational and software development management
Collaborate on team strategy, set goals, and provide technical direction while fostering growth
Partner with cross-functional teams (science, engineers, and operations) to align initiatives
Contribute to core decisions on tools, infrastructure, and architectural design
Build and operate processes and tools for effective operational management of research and production software and to enable and enhance effective software development practices
Qualifications
Cloud Infrastructure: Proven experience in building, deploying, and maintaining production systems on major cloud platforms, with a preference for Google Cloud Platform (GCP)
Containerization and Orchestration: Proficiency with Docker and Kubernetes/KubefLow for containerization and orchestration, ensuring efficient deployment and scaling of applications
Infrastructure as Code (IaC): Strong understanding of IaC principles, utilizing tools like Terraform to manage and provision cloud resources
Continuous Integration/Continuous Deployment (CI/CD): Experience with CI/CD pipelines and release management, employing tools such as GitLab CI, GitHub Actions, or CircleCI to automate testing and deployment processes
Programming Skills: Advanced proficiency in Python programming, complemented by experience in shell scripting, enabling effective automation and integration tasks
Deployment Tools: Familiarity with deployment tools like Helm, Kustomize, or Kapitan to manage Kubernetes configurations and streamline application releases
Monitoring and Observability: Experience with monitoring and observability tools such as Grafana, Prometheus, or Splunk to ensure system reliability and performance
Security Awareness: Ability to identify security risks within cloud infrastructures and implement measures to mitigate them, ensuring robust and secure systems
Platform Development: Demonstrated experience in building secure and scalable platforms or products in cloud environments, emphasizing best practices in architecture and design
Site Reliability Engineering (SRE) and DevOps Practices: Practical experience with modern SRE and DevOps lifecycles, tools, and frameworks, fostering a culture of automation and continuous improvement
Adaptability and Hands-on Approach: Pragmatic and flexible, willing to engage directly in technical tasks when necessary to achieve team objectives
Preferred Qualifications
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.
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