Senior Machine Learning Engineer

The role

You will design, build, and operate production machine learning systems. This includes work on personalization, recommendations, optimization, and shared ML platforms.

What you will do

• Design, build, and operate end-to-end machine learning systems across batch and real-time workloads.
• Develop production capabilities for personalization, recommendations, ranking, optimization, contextual decisioning, experimentation, and measurement.
• Build reusable ML platforms, pipelines, frameworks, and tooling.
• Own the operational lifecycle of production models including observability, quality, and monitoring.
• Partner with ML practitioners and Data and Product teams to integrate systems into products.
• Provide technical leadership for ML architecture and distributed systems.

Required qualifications

• 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.
• Strong collaboration and communication skills.
• A commitment to raising the technical capabilities of the broader team through mentorship, review, documentation, and shared engineering practices.
• U.S. core business hours availability.

Nice to have

• 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.

Benefits

• Flexible PTO, with a minimum requirement to take one day off a quarter, ten days a year
• 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

About the company

Kard is building commerce media infrastructure that connects financial institutions, financial-services platforms, and merchants through data and merchant-funded rewards.