Senior Software Engineer - Model Platform
About the Role
Abnormal AI is looking for a Senior Software Engineer to join the Detection Team. The Detection Division is focused on building the world’s most advanced technology for identifying and stopping email and cloud-based attacks that were previously undetectable and helping make the world a safer place. As a Senior Software Engineer building systems for Detection’s Signals and Serving Team, you will make feature development at Abnormal fast, responsive, stable, and confident for our ML and Data Science team. The ideal candidate would have the following qualities:
- A first principles approach to building scalable, customer-centric solutions
- A drive to solve meaningful & pragmatic problems for real-world people
- An ownership and impact-oriented outlook on your efforts and growth
- An ability to iterate in real-time-solving novel problems, quickly and autonomously
An ability to iterate in real-time - solving novel problems, quickly and autonomously
What you will do
- Architect, design, build, deploy, and maintain Model Serving infrastructure that supports a world-class Detection Engine
- Own projects that scale our model serving and data processing services to handle 10x the traffic we serve today
- Build the platform for fighting against rapidly generated AI attacks
- Own real-time, near real-time streaming pipelines, and online feature serving services
- Build Abnormal’s ML Training platform, improving MLE velocity and product precision and recall
- Collaborate closely with MLE and Data Science teams by distilling feedback, correlating it to strategy, and executing
- Coach and mentor junior engineers via 1on1s, pair programming, high-quality code reviews, and design reviews
Must Haves
5+ years of experience
as a Software Engineer or in a similar role, with hands-on experience in building ML-engineering focused solutions.
- Experience maintaining
large-scale distributed systems on cloud platforms
such as AWS, GCP, or Azure, including a strong grasp of cloud-based engineering best practices.
- Experience with maintaining
real-time and near real-time
Proven ability to collaborate effectively
Excellent problem-solving skills
and the ability to work independently in a fast-paced environment. You can break down complex challenges into manageable steps and iterate on solutions, balancing immediate needs with long-term scalability.
- Familiarity with
machine learning
workflows and requirements to support MLE teams effectively. This includes feature development and serving at 50K+ QPS, offline/online equivalency, large batch jobs for data gathering and training of tree and deep learning models.
- Experience with
streaming data architectures
and real-time processing.
- Knowledge of
security and compliance
Not included in the source posting: about the role, benefits.
Skills
Who can apply
The employer didn't state any visa, work authorization, citizenship or clearance requirements in this posting. Confirm with the employer before applying.
Read automatically from the employer's posting text. Always confirm with the employer — requirements can change after a job is published.