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 production development and ongoing operations of high‑profile ML products.

This role has no direct people‑management responsibilities but is accountable for technical strategy, operational maturity, engineering standards, platform capabilities, and the long‑term effectiveness of the ML software engineering practice.

You will balance strategic leadership with hands‑on technical contribution, setting technical direction and participating in architecture, design and code reviews, as well as selective implementation efforts.

• What You’ll Own
• Define the technical vision and strategy for ML software engineering initiatives, aligning them with business goals.
• Develop scalable capabilities to power real‑time decisioning engines throughout the payment lifecycle and beyond.
• Enable rapid experimentation while ensuring robust, scalable, and secure deployment of ML solutions.
• Establish and evolve engineering standards, operating practices, and technical governance.
• Mentor engineers, provide technical coaching, and promote technical excellence.
• Champion collaboration, continuous improvement, and knowledge sharing.
• Drive alignment across teams through technical influence and architectural guidance rather than direct management authority.
• Identify capability gaps and drive improvements to tooling, automation, observability, and operational processes.
• Establish operational standards for production ML systems, including reliability objectives, observability, incident management, and support processes.
• Guide the architecture, implementation, deployment, and operation of ML products and reusable components.
• Ensure systems and components meet requirements for scalability, latency, explainability, and regulatory compliance.
• Contribute to QA and code as needed.
• Partner closely with research‑focused data science teams, business stakeholders, infrastructure support teams, data engineering teams, security/compliance teams, and others to identify opportunities and incorporate ML into products and systems.
• Collaborate with other data science and engineering leaders to establish an operating model for machine learning R&D that optimizes end‑to‑end delivery of business value.
• Communicate complex technical concepts to non‑technical stakeholders effectively.
• What You’ll Bring
• Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Engineering, or a related field (Ph D a plus).
• 7+ years of ML software engineering, ML ops, ML engineering, or ML research experience.
• 5+ years of experience deploying large‑scale, real‑time ML models in customer‑facing, production environments, including significant hands‑on experience.
• 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 Data Bricks.
• Strong understanding of the data science/ML research process.
• Strong understanding of software engineering, MLOps, and Dev Ops best practices.
• Strong Python skills, including Pandas, Num Py, scikit‑learn.
• Proficiency in SQL and No SQL databases.
• Excellent communication, leadership, and stakeholder management skills.
• It’s a Bonus if You Have
• Experience in a merchant acquiring, payment service provider, or card network environment.
• Familiarity with tokenization, real‑time payments, and the authorization lifecycle.
• Experience in a large, complex organization in a highly regulated industry.
• Experience working in an agile environment.
• Why Join Us
• Impact: Play a key role as the technical owner of high‑profile ML products delivering meaningful business impact to merchants and advancing key pillars of the company’s strategy.
• Autonomy: Take end‑to‑end technical ownership of your product area, with the freedom and responsibility to drive technical solutions, shape best practices, and deliver results in a fast‑paced, supportive environment.
• Collaboration: Join a cross‑functional, high‑performing team where your expertise is valued and your contributions make a real difference.
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