Senior DevOps Engineer - AI & Data Infrastructure

At Goodnotes, we believe that every individual holds untapped potential waiting to be unleashed. By reimagining the way we interact with information, we’re merging human creativity with the breakthrough capabilities of AI. Our renewed vision and mission drive us to create the best medium for human and AI collaboration, empowering users to explore new dimensions of productivity, creativity, and learning. Join us on this journey as we transform digital note-taking into an inspiring and innovative experience.

AI team in Goodnotes is looking to transform education and productivity using the latest technologies. We are working on helping students and teachers learn and teach more efficiently, and aim to achieve this by developing tools for Goodnotes AI and more foundational technologies like subject-oriented handwriting recognition.
You will join a distributed team across Europe and Asia focusing specifically on building backend infrastructure for running our end-to-end AI technology. You will work alongside other backend software engineers, as well as iOS engineers, machine learning engineers, QAs and designers to build and improve our new suite of AI features. Type of AI technologies running on our infrastructure include large language models, math solvers, handwriting recognition systems, etc. Besides models, our backend engineering team is building a holistic data engineering pipeline for training and production data.

We are seeking an experienced and passionate software engineer to help us build our AI and data infrastructure. This person will work on building the end-to-end data pipeline, both in production and for training, as well as the infrastructure for training, hosting and running our ML models in production (on the cloud, on our servers and on-device).
This is the role for you, if you’re excited to work on the things listed below:

• Build and maintain end-to-end backend infrastructure for training and running our models in production
• Design and build components within data pipelines for collecting production data
• Data engineering for efficient ingestion of data for the model training and evaluation
• Helping the team build and maintain compute training and inference infrastructure
• Monitoring the production and setting up alerting mechanisms

The skills you will need to be successful in the above:

• 7+ years of software engineering experience, notable part of it being in the data engineering space
• Experience with designing and building data or training pipelines
• Previous experience in designing, building and maintaining cloud infrastructure to support machine learning operations
• Experience in LLM backend design and operation, including monitoring, optimization at a large scale.
• Experience with working in Python and basic understanding of the ML ecosystem, including but not limited to Pytorch, ONNX, TensorRT
• Excellent problem-solving skills and ability to think critically.
• Desire to work in a fast-paced, collaborative environment.
• Excellent communication skills, both verbal and written.

Even if you don’t meet all the criteria listed above, we would still love to hear from you! Goodnotes places a lot of value on learning and development and will support your growth if needed.
The interview process:

• An introductory call with someone from our talent acquisition team. They want to hear more about your background, what you are looking for, and why you’d like to join Goodnotes
• Take-home Assignment: A challenge to demonstrate your general Ops skills.
• Technical interview: Discussion of your submissions, short hands-on exercises and technical questions on ML Ops and Data Ops with a team member.
• Hiring Manager interview: A call with your hiring manager. This is the person who will be managing you day to day, working on your growth and development with you as well as support you throughout your career at Goodnotes.
• Panel interview – Meeting with members of the Goodnotes Team to answer questions relating to take ownership AND build great things

What’s in it for you:

• Meaningful equity in a profitable tech startup
• Budget for things like noise-cancelling headphones, setting up your home office, personal development, professional training, and health & wellness
• Sponsored visits to our Hong Kong or London office every 2 years
• Company-wide annual offsite (we met in Portugal in 2023 and Bali in 2024)
• Flexible working hours and location
• Medical insurance for you and your dependents

Note: Employment is contingent upon successful completion of background checks, including verification of employment, education, and criminal records.