Staff Backend Software Engineer - ML Systems Integration

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.

As a remote-first company, Socure fosters a culture of autonomy, collaboration, and continuous learning. Our teams are empowered to take ownership, move fast, and build technology that drives real-world change. Recognized by Forbes, Deloitte, and Inc. as one of the fastest-growing and most innovative companies in tech, we’re just getting started–come join us.

Explore SocureLife and help us redefine digital trust.

We are seeking a highly skilled Staff Backend Engineer with deep expertise in backend software engineering and hands-on experience deploying and integrating machine learning models into production systems. This role will play a pivotal part in scaling our document verification platform, supporting both traditional backend services and the operationalization of ML models developed by our Data Science team.

You will collaborate cross-functionally with Data Science, Infrastructure, and Product teams to design scalable APIs, build robust pipelines, and ensure reliable, observable, and performant model deployments. This is an ideal role for an engineer who thrives at the intersection of software engineering and applied machine learning.

Key Responsibilities

• Backend Architecture & Development: Design and implement scalable, maintainable backend services using Java or Go.

• ML Model Integration: Work closely with Data Scientists to deploy, serve, and monitor ML models (TorchServe, Flask, or SageMaker).

• System Design: Lead design discussions and planning for backend services that incorporate model inference, SQL/NoSQL and Graph databases, and metadata tracking.

• Infrastructure & Observability: Partner with infrastructure engineers to ensure secure, observable, and performant deployments.

• Model Lifecycle Support: Build tools and services to support model versioning, performance monitoring, and rollback mechanisms.

• Cross-Functional Collaboration: Serve as a bridge between Data Science and Backend Engineering teams to ensure alignment and delivery.

• Technical Leadership: Mentor junior engineers, drive engineering best practices, and lead technical initiatives across teams.

• 8+ years of backend software engineering experience

• Strong command of Java or Go (ideally both)

• Experience designing and building distributed systems

• Production experience deploying ML models (TorchServe and/or SageMaker)

• Familiarity with SQL/NoSQL and Graph databases

• AWS experience: S3, Lambda, ECS, SQS, CloudWatch

• Strong knowledge of system observability: logging, tracing, metrics

• Comfortable designing CI/CD pipelines (GitHub Actions, Jenkins, etc.)

• Experience with TorchServe GPU tuning and resource optimization

• Model performance monitoring experience

• Familiarity with ML experimentation tools or data versioning (e.g., MLflow, DVC)

• Exposure to internationalization/NLP or document image extraction pipelines

• Experience with SageMaker pipelines or model migration to managed ML services

• Experience with AWS SageMaker

This represents the expected salary range for this job requisition. Final offers may vary from the amount listed based on factors including geography, candidate experience and expertise, and other job related factors. Socure's compensation and rewards package for full time roles includes a market competitive salary, equity,  comprehensive benefits, and, for applicable roles, commissions plans or an annual discretionary performance bonus. 

Explore SocureLife to learn more and check out Socure’s Career Page.