Kard is building commerce media infrastructure that connects financial institutions, financial-services platforms, and merchants through data and merchant-funded rewards. As our reach expands, we are building for a step-change in scale, and for opportunities ranging from more relevant rewards and marketer intelligence to new commerce and distribution models.
As a Senior Machine Learning Engineer, you will design, build, and operate the production systems that turn machine learning into durable product capabilities. Your scope will span personalization and recommendations, optimization and decisioning, experimentation and measurement infrastructure, model training and serving, and the shared platforms and tooling that support ML development at Kard.
This is a senior individual-contributor role on the Data team, reporting to the Director of Data & Platform. You will work primarily with other machine learning engineers and data scientists, while partnering across Data and Product to move models from experimentation through deployment and ongoing operation. You will also provide technical leadership through architecture, engineering standards, mentorship, and design and code review.
Responsibilities- Design, build, and operate end-to-end machine learning systems across batch and real-time workloads, including feature generation, training, evaluation, deployment, inference, and retraining.
- Develop production capabilities for personalization, recommendations, ranking, optimization, contextual decisioning, experimentation, and measurement.
- Build reusable ML platforms, pipelines, frameworks, and tooling that improve reproducibility, self-service, reliability, and development speed.
- Own the operational lifecycle of production models, including observability, data and model quality, drift detection, performance monitoring, failure handling, retraining, and governance.
- Partner with other ML practitioners to turn prototypes and research into maintainable systems, and with Data and Product teams to integrate those systems into Kard’s products and platform.
- Provide technical leadership for ML architecture and distributed systems, making pragmatic tradeoffs among model performance, reliability, scalability, development speed, and operational complexity.
- 8+ years of professional software engineering or machine learning engineering experience.
- A strong record of building, deploying, and operating machine learning systems in production.
- Strong software engineering fundamentals, including system design, APIs, testing, deployment, observability, and maintainable production code.
- Experience designing distributed systems, large-scale data-processing workflows, or high-throughput and low-latency services.
- Fluency across the ML lifecycle, including data and feature pipelines, training, evaluation, model serving, monitoring, and retraining.
- The ability to investigate production issues across models, data, application code, and infrastructure.
- The judgment and autonomy to lead technically complex work, navigate ambiguity, and make architectural decisions with long-term consequences.
- Strong collaboration and communication skills, particularly when working across machine learning, data engineering, analytics, and product disciplines.
- A commitment to raising the technical capabilities of the broader team through mentorship, thoughtful review, documentation, and shared engineering practices.
- Demonstrated experience matters more to us than a particular degree or industry background.
- U.S. core business hours availability and willingness to travel for company meetings.
- Experience with personalization, recommendation, ranking, optimization, experimentation, measurement, or real-time decisioning systems.
- Experience with technologies such as Python, Apache Spark, Databricks, MLflow, feature stores, or model-serving platforms.
- Experience operating ML workloads on AWS, Kubernetes or Amazon EKS, and infrastructure managed through Terraform.
- Experience building ML systems at enterprise, transaction-intensive, or regulated scale.
Kard recognizes the unique value each of us brings to our collective success. As part of our remote-first team, you'll have the autonomy to influence our trajectory, actively contributing to the growth of our business and the evolution of our company culture. By embodying our core values of Initiative, Openness, and Humility, you will not only witness but directly foster an inclusive and dynamic work environment, from the executive level down.
Our competitive benefit plan includes:- Flexible PTO, with a minimum requirement to take one day off a quarter, ten days a year, promoting mental well-being
- Observance of 11 Federal Holidays, plus an additional day each for Black Friday and Christmas Eve (US employees only)
- Health, Dental and Vision Insurance
- 401k with employer match (US employees only)
- Coworking space and WFH setup reimbursement
- Company Offsites for planning, team-building, and networking
Skills Required
- 8+ years of professional software engineering or machine learning engineering experience
- Proven experience building, deploying, and operating machine learning systems in production
- Strong software engineering fundamentals, including system design, APIs, testing, deployment, observability, and maintainable production code
- Experience designing distributed systems, large-scale data-processing workflows, or high-throughput and low-latency services
- Fluency across the machine learning lifecycle, including feature pipelines, training, evaluation, model serving, monitoring, and retraining
- Ability to investigate production issues across models, data, application code, and infrastructure
- Ability to lead technically complex work, navigate ambiguity, and make architectural decisions
- Strong collaboration and communication skills across machine learning, data engineering, analytics, and product teams
- Commitment to mentorship, thoughtful review, documentation, and shared engineering practices
- Availability during U.S. core business hours
- Willingness to travel for company meetings
- Experience with personalization, recommendation, ranking, optimization, experimentation, measurement, or real-time decisioning systems
- Experience with Python, Apache Spark, Databricks, MLflow, feature stores, or model-serving platforms
- Experience operating machine learning workloads on AWS, Kubernetes, or Amazon EKS
- Experience managing infrastructure through Terraform
- Experience building machine learning systems at enterprise, transaction-intensive, or regulated scale
What We Do
Kard’s rewards-as-service platform makes loyalty more rewarding by simplifying the rewards experience for cardholders, financial institutions, and merchants. Utilizing the Kard API, financial institutions — including neobanks, traditional banks, and any other card issuer — can quickly and easily build their own customizable rewards program, driving cardholder engagement and loyalty by connecting users to the brands they love and rewarding them for everyday purchases. Powering rewards for over 45 million cardholders in the Kard issuer and partner network, Kard drives new customer acquisition and loyalty for thousands of in-store and online merchants across the US. Learn more at www.getkard.com.
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