At Socure , we’re on a mission—to verify 100% of good identities in real time and eliminate identity fraud from the internet.
Using predictive analytics and advanced machine learning trained on billions of signals to power RiskOS™, Socure has created the most accurate identity verification and fraud prevention platform in the world. Trusted by thousands of leading organizations—from top banks and fintechs to government agencies—we solve real, high-impact problems at scale. Come join us!
As a Senior Software Engineer on Socure’s AI Platform team, you’ll design and build infrastructure that supports model training, validation, deployment, and serving at scale. You will work with modern AWS-native technologies, focusing on low-latency microservices, automated pipelines, and robust deployment workflows to enable safe and efficient delivery of machine learning models into production.
This role is ideal for someone who enjoys building platforms and tools that abstract complexity for ML and data science teams, and who thrives in fast-paced environments where engineering excellence and reliability are paramount.
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.
Participate in code reviews, system design, and platform roadmap discussions.
Continuously improve deployment reliability, speed, and usability of the ML platform.
4+ years of experience as a software engineer, with at least 2 years focused on low latency and highly available backend systems.
Bachelor’s or Master’s degree in Computer Science, Data Science, AI, Machine Learning, or a related field with a strong academic record.
Strong fundamentals in data structures, algorithms, and distributed computing principles.
Strong analytical and problem-solving skills, with a passion for AI and machine learning.
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).
Experience building internal ML platform services or self-service tooling for model deployment and monitoring.
Understanding of model optimization techniques (e.g., TorchScript, ONNX, quantization, batching).
Experience with feature stores, real-time feature serving, or caching systems for ML workloads.
Background in deploying ML models into high-availability, mission-critical environments.
Please note that Socure cannot provide sponsorship now or in the future for this opening .
Socure is an equal opportunity employer and values diversity of all kinds at our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
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