Software Engineer - ML Platform

<div class="p-rich_text_section"> <p>The ML Platform team at Veriff builds the foundation for rapid, compliant, and reliable iteration on machine learning products. We provide the scalable, observable, and user-friendly systems required to manage data, train models, evaluate performance, and deploy models at scale.</p> <p>Having already established our core platform capabilities, we are now entering a high-growth phase focused on <strong>systemic excellence</strong>: institutionalizing world-class observability, optimizing for cost-efficiency, and radicalizing our experimentation speed. Your role will help us bridge the gap between architectural vision and a seamless developer experience for our data science teams.</p> <h4><strong>You’ll help us enable ML innovation by:</strong></h4> <ul> <li>Implementing Observability Frameworks: Building the tools and templates that provide visibility into model performance, data drift, and training statistics, ensuring our continuous retraining loops are robust.</li> <li>Engineering for Efficiency: Developing systems to track and optimize compute costs and training performance, allowing us to scale our ML efforts sustainably.</li> <li>Building Experimentation Tooling: Executing on the roadmap for internal tools that enable Data Scientists and ML Engineers to iterate and deploy experiments with minimal friction.</li> <li>Developing SaaS-grade ML Services: Writing high-quality, maintainable Python code to build and automate services that sit at the core of our ML lifecycle.</li> <li>Bridge-Building: Working alongside our Staff Engineer to implement architectural designs and collaborating with SRE/DevXP teams to ensure our solutions are production-ready and easily managed.</li> </ul> <h4><strong>You are the right future Veriffian for the job if you have:</strong></h4> <ul> <li>3+ years of experience in software or ML engineering, specifically building tools that support the ML lifecycle (MLOps).</li> <li>Strong Python skills with experience in building internal APIs or automation services.</li> <li>Hands-on experience with the open-source ML stack (e.g., MLflow, Kubeflow, Ray, or Prometheus/Grafana for ML monitoring).</li> <li>A "Product" mindset for internal tools: You care about the developer experience of the Data Scientists using your platform.</li> <li>Experience with SQL and Data Engineering (e.g., Snowflake, Spark, or dbt) to understand how data flows into our training pipelines.</li> <li>A skeptical, first-principles approach to engineering—you prefer understanding the "why" behind a system rather than just following a vendor's tutorial.</li> </ul> </div> <div class="p-rich_text_section"><strong data-stringify-type="bold">Why Veriff?</strong></div> <div class="p-rich_text_section"> </div> <div class="p-rich_text_section"> <div class="p-rich_text_section">We are the preferred identity verification platform partner for the world’s most innovative growth-driven organizations helping conveniently verify and safeguard users anywhere in the world. We support the broadest number of identity documents from nearly every country and territory in the world - and this is continually increasing! With a diverse team in the United States, United Kingdom, Spain, and Estonia, as well as robust backing and funding from investors including Accel, Alkeon, IVP, Tiger Capital, and Y Combinator, we’re dedicated to helping businesses and individuals build a safer and more secure world. We strive to be the benchmark for trust online, and we take pride in being a positive force. </div> <div class="p-rich_text_section"> </div> <div class="p-rich_text_section">When you join Team Veriff, we offer you the opportunity to have a real impact and advance your career, while looking after you along the way with a range of benefits designed with you in mind. Some of our favorites include...</div> <ul class="p-rich_text_list p-rich_text_list__bullet" data-stringify-type="unordered-list" data-indent="0" data-border="0"> <li ... (truncated, view full listing at source)