Abnormal Security · Remote · United States
Join Abnormal AI, a leading company in the fight against email and cloud-based attacks. As a Senior Software Engineer, you will be responsible for building and maintaining the Model Serving infrastructure that supports our world-class Detection Engine. You will work closely with cross-functional teams, including data scientists and machine learning engineers, to drive feature development and improve product precision and recall. This position offers a range of benefits, including healthcare, flexible PTO, and a home office stipend.
- An ability to iterate in real-time - solving novel problems, quickly and autonomously
- A first principles approach to building scalable, customer-centric solutions
- A drive to solve meaningful & pragmatic problems for real-world people
- An ability to iterate in real-time-solving novel problems, quickly and autonomously
- An ownership and impact-oriented outlook on your efforts and growth
- Proven ability to collaborate effectively with cross-functional teams, including data scientists, machine learning engineers, product managers, and other stakeholders. You can translate requirements into actionable technical tasks, communicate progress clearly, and adapt to feedback
- 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
- 5+ years of experience as a Software Engineer or in a similar role, with hands-on experience in building ML-engineering focused solutions
- Knowledge of security and compliance frameworks as they relate to data engineering and data privacy
- Experience with streaming data architectures and real-time processing
- 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 data pipelines or streaming services at high scale
- 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
- This position involves access to technology that is subject to the U.S. Export Administration Regulations (EAR). As a result, candidates offered employment must be eligible to access controlled technology under U.S. export control laws. Employment in this position is conditioned on the availability of government authorization