Software Engineer - ML Platform

About Veriff and the ML Platform Team

Veriff is a leading identity verification platform, partnering with innovative growth-driven organizations worldwide to safeguard users. With a diverse team spanning the United States, United Kingdom, Spain, and Estonia, and strong backing from investors like Accel and Y Combinator, Veriff is committed to building a safer and more secure online world.

The ML Platform team at Veriff is crucial for enabling rapid, compliant, and reliable iteration on machine learning products. They establish the foundational systems for data management, model training, performance evaluation, and scalable model deployment. Having built core capabilities, the team is now focused on systemic excellence, enhancing observability, optimizing cost-efficiency, and accelerating experimentation speed. This role aims to bridge architectural vision with a seamless developer experience for data science teams.

What You'll Help Us Achieve

• Implement Observability Frameworks: Develop tools and templates to provide critical visibility into model performance, data drift, and training statistics, ensuring the robustness of continuous retraining loops.
• Engineer for Efficiency: Create systems to track and optimize compute costs and training performance, supporting sustainable scaling of ML initiatives.
• Build Experimentation Tooling: Execute the roadmap for internal tools, enabling Data Scientists and ML Engineers to iterate and deploy experiments with minimal friction.
• Develop SaaS-grade ML Services: Write high-quality, maintainable Python code to build and automate core services within the ML lifecycle.
• Bridge Architectural Gaps: Collaborate with Staff Engineers on architectural designs and work alongside SRE/DevXP teams to ensure production-readiness and easy management of solutions.

What Makes You the Right Veriffian for This Role

• 3+ years of experience in software or ML engineering, specifically building tools that support the ML lifecycle (MLOps).
• Strong Python skills, including experience in building internal APIs or automation services.
• Hands-on experience with the open-source ML stack (e.g., MLflow, Kubeflow, Ray, or Prometheus/Grafana for ML monitoring).
• A "Product" mindset for internal tools, prioritizing the developer experience for data scientists.
• Experience with SQL and Data Engineering (e.g., Snowflake, Spark, or dbt) to understand data flow into training pipelines.
• A skeptical, first-principles engineering approach, valuing understanding the "why" behind systems.

Why Join Team Veriff?

Joining Veriff offers the opportunity to make a significant impact and advance your career. We provide a range of benefits tailored to your well-being and growth:

• Flexibility to work from home.
• Stock options to share in Veriff's success.
• Extra recharge days in addition to annual vacation.
• Comprehensive relocation support to Estonia or Spain.
• Extensive medical, dental, and vision insurance.
• Learning and Development & Health and Sports budget.
• Four weeks of fully paid sabbatical leave after 5 years.

Veriff is an Equal Opportunities employer, committed to a diverse and representative team, valuing different opinions and perspectives. We encourage all passionate and aligned candidates to apply.

Key skills/competency

• MLOps
• Python
• Machine Learning Engineering
• Observability
• Data Pipelines
• Experimentation
• System Design
• Cloud Platforms
• Developer Experience
• Data Engineering