Senior Software Engineer - Model Platform
$180k - $259k • Remote • Remote - USA
Posted 1d ago
Job Location
Remote - USA
Tech Stack
Remote Work Policy
Fully remote
Categories
Machine Learning Engineer
About the job
Abnormal AI is seeking a Senior Software Engineer to join the Detection Team, focused on building advanced technology to identify and stop email and cloud-based attacks. In this role, you will enhance the speed, responsiveness, stability, and confidence of feature development for the ML and Data Science teams. The ideal candidate possesses a first-principles approach to scalable, customer-centric solutions, a drive to solve meaningful problems, and an ownership-oriented outlook, with the ability to iterate quickly and autonomously on novel challenges.
Responsibilities
- Architect, design, build, deploy, and maintain Model Serving infrastructure for the Detection Engine.
- Scale model serving and data processing services to handle significant traffic increases.
- Develop the platform for combating rapidly generated AI attacks.
- Own real-time, near real-time streaming pipelines, and online feature serving services.
- Build the ML Training platform to enhance MLE velocity and product precision/recall.
- Collaborate with MLE and Data Science teams by gathering feedback, aligning it with strategy, and executing tasks.
- Coach and mentor junior engineers through 1on1s, pair programming, code reviews, and design reviews.
Requirements
- 5+ years of experience as a Software Engineer or similar role, with hands-on experience in ML-engineering solutions.
- Experience maintaining large-scale distributed systems on cloud platforms (AWS, GCP, Azure) and cloud-based engineering best practices.
- Experience maintaining real-time and near real-time data pipelines or streaming services at high scale.
- Proven ability to collaborate effectively with cross-functional teams (data scientists, ML engineers, product managers, stakeholders).
- Excellent problem-solving skills and ability to work independently in a fast-paced environment.
- Familiarity with machine learning workflows and requirements to support MLE teams (feature development/serving at 50K+ QPS, offline/online equivalency, large batch jobs).
- Experience with streaming data architectures and real-time processing.
- Knowledge of security and compliance frameworks related to data engineering and privacy.
Benefits
- Bonus or incentive compensation
- Equity
- Comprehensive benefits package