ML Software Engineering Lead

We are seeking an experienced and visionary ML Software Engineering Lead to serve as the technical and functional leader for the Data Science Enablement engineering function, owning the production development and ongoing operations of high-profile ML products. This role balances strategic leadership with hands-on technical contribution, guiding the architecture, design, and deployment of ML solutions while collaborating closely with product, data science, platform engineers, and other teams.

Responsibilities

• Strategy and Vision: Define the technical vision and strategy for ML software engineering initiatives, align them with business goals, develop scalable real-time decisioning engines, enable rapid experimentation with robust, scalable, and secure deployment.
• Engineering and Operational Excellence: Establish engineering standards, operating practices, and technical governance; mentor engineers; promote continuous improvement and knowledge sharing; drive tooling, automation, observability, and operational process improvements; enforce reliability, observability, incident management, and support standards.
• Technical Leadership and Contribution: Guide architecture, implementation, deployment, and operation of ML products and reusable components; ensure scalability, latency, explainability, and regulatory compliance; promote best practices; stay abreast of industry trends; contribute to QA and code as needed.
• Cross-Functional Collaboration: Partner with research-focused data science teams, business stakeholders, infrastructure support, data engineering, security/compliance teams; collaborate with other leaders to establish an operating model for machine learning and communicate complex technical concepts to non-technical stakeholders.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Engineering, or related field (PhD a plus).
• 7+ years of ML software engineering, ops, engineering, or research experience.
• 5+ years of experience deploying large-scale, real-time ML models in customer-facing production environments.
• 2+ years of technical leadership experience on an early-stage ML software engineering team.
• 2+ years of data science research experience.
• Proven experience developing microservices at scale (API design, monitoring, deployment strategies, containerization) in a cloud environment, preferably AWS and Databricks.
• Strong understanding of the data science/ML research process, software engineering, MLOps, and DevOps best practices.
• Strong Python skills, including Pandas, NumPy, scikit-learn; proficiency in SQL and NoSQL databases.
• Excellent communication, leadership, and stakeholder management skills.

Bonus: Experience in merchant acquiring, payment service provider, or card network; tokenization, real-time payments, authorization lifecycle; large regulated industry; agile environment.

Benefits

• Impact: Technical ownership of high-profile ML products delivering business impact to merchants.
• Autonomy: End-to-end technical ownership, freedom to drive solutions and shape best practices.
• Collaboration: Cross-functional high-performing team where expertise is valued and contributions make a real difference.