Socure is building the identity trust infrastructure for the digital economy — verifying 100% of good identities in real time and stopping fraud before it starts
Requirements
- Strong fundamentals in data structures, algorithms, and distributed computing principles
- Strong programming skills in Python; familiarity with Go/Rust is a plus
- Hands-on experience with model systems including low latency model serving, registry, and pipeline orchestration(preferably SageMaker)
- Solid understanding of MLOps best practices, including model versioning, testing, deployment, and reproducibility
- Experience building and maintaining CI/CD pipelines for ML workflows
- Experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn
- Experience with database technologies (SQL, NoSQL, or data warehouses like Snowflake or Redshift)
Responsibilities
- Build and maintain scalable systems and infrastructure for deploying and serving ML models
- Design low-latency, fault-tolerant model inference systems using Amazon SageMaker
- Implement safe deployment strategies like blue/green deployments and rollbacks
- Create and manage CI/CD pipelines for ML workflows
- Monitor model performance and system health using AWS observability tools (e.g., CloudWatch)
- Develop internal tools and APIs to help ML teams deploy and monitor models easily
- Collaborate with ML engineers, data scientists, and DevOps to productionize new models
Other
- Bachelor’s or Master’s degree in Computer Science, Data Science, AI, Machine Learning, or a related field with a strong academic record
- 4+ years of experience as a software engineer, with at least 2 years focused on low latency and highly available backend systems
- Strong analytical and problem-solving skills, with a passion for AI and machine learning
- Please note that Socure cannot provide sponsorship now or in the future for this opening
- Socure is an equal opportunity employer that values diversity in all its forms within our company
