Senior Engineer - ML Ops and Devops
Founded in 2015, Acubed is the Silicon Valley innovation center of Airbus. As a global leader in aerospace, Airbus aims to make things fly. Our mission is to provide a lens into the future for the industry, transforming risk into opportunity to build the future of flight now.
At Acubed, we strive to propel innovation to market faster, broaden the talent pool in emerging aerospace careers and simultaneously help drive a culture change across Airbus.
Project Wayfinder is building scalable, certifiable autonomy systems to power the next generation of commercial aircraft. Our team of experts is driving the maturation of machine learning and other core technologies for autonomous flight; we are creating a reference architecture that includes hardware, software, and a data-driven development process to allow aircraft to perceive and react to their environment. Autonomous flight is transforming the transportation industry, and our team is at the heart of this revolution.
As part of the DevOps and Site Reliability team you will be supporting new and existing Devops and MLOps needs. This includes interacting with internal teams to make sure we support all their Devops, MLOps, CI/CD requests, this means that you will be responsible for designing, maintaining and evolving the Development Operations at Wayfinder.
You will be involved in a fast-paced development environment characterized by state-of-the-art autonomy development and will be responsible for making sure our teams are as efficient as possible.
As part of this role you will act as an architect, helping us reach the maximum productivity while allowing the team to minimize code bugs by implementing a full devops/mlops pipeline.
- Design, implement and maintain the Wayfinder DevOps and MLOps stack
- Support the site reliability operations at Wayfinder.
- Support the infrastructure and devops team on making sure we have a scalable and highly available software development environment.
- Interface with internal teams to understand requirements, provide solutions and propose usage best practices
- Work with the infrastructure vendors to scale our infrastructure needs.
- Bachelor’s degree in computer science, computer engineering or a related discipline
- 2 years of professional experience in building devops and CI/CD pipelines
- Experience with cloud infrastructure (e.g., GCP, AWS)
- Experience deploying ML Ops pipelines (eg. Weights and Biases, Tensorboard, Tableau, Run.ai etc)
- Experience evaluating and dealing with 3rd party tool vendors
- Documented proof of fully vaccinated status required (or qualify for an exemption)
- Experience working on infrastructure teams focused on autonomous vehicle or other ML applications
- Computer vision ML pipeline design and implementation experience
- Exceptional PPO medical, dental and vision benefits 100% of premiums covered for employee and their family/dependents
- Generous PTO of 5 weeks (6 weeks after two years) in addition to 11 national holidays and unlimited paid sick days
- Tuition reimbursement for professional development or $15,750 for flight training
- 3 months paid parental leave from Day 1