Senior Machine Learning Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, construct, and manage comprehensive machine learning systems for both batch and real-time tasks, encompassing feature generation, training, evaluation, deployment, inference, and retraining.

• Create production capabilities for personalization, recommendations, ranking, optimization, contextual decision-making, experimentation, and measurement.

• Develop reusable ML platforms, pipelines, frameworks, and tools to enhance reproducibility, self-service, reliability, and development speed.

• Take ownership of the operational lifecycle of production models, which includes observability, data and model quality, drift detection, performance monitoring, failure management, retraining, and governance.

• Collaborate with ML practitioners to transform prototypes and research into sustainable systems.

• Work alongside Data and Product teams to integrate ML systems into Kard’s products and platforms.

• Provide technical leadership in ML architecture and distributed systems, ensuring a balance between model performance, reliability, scalability, development speed, and operational complexity.

• Report to the Director of Data & Platform while offering mentorship, documentation, and conducting design and code reviews.

⛳️ Requirements

• Over 8 years of professional software engineering or machine learning engineering experience.

• Proven track record of building, deploying, and managing machine learning systems in a production environment.

• Solid software engineering fundamentals, including system design, APIs, testing, deployment, observability, and maintainable production code.

• Experience in designing distributed systems, large-scale data-processing workflows, or high-throughput and low-latency services.

• Proficiency across the ML lifecycle, covering data and feature pipelines, training, evaluation, model serving, monitoring, and retraining.

• Capability to investigate production issues across models, data, application code, and infrastructure.

• Sound judgment and autonomy to lead technically complex tasks, navigate uncertainty, and make long-term architectural decisions.

• Strong collaboration and communication abilities across machine learning, data engineering, analytics, and product disciplines.

• Dedication to enhancing the technical capabilities of the broader team through mentorship, thoughtful reviews, documentation, and shared engineering practices.

• Availability during U.S. core business hours and willingness to travel for company meetings.

🏝️ Benefits

• Flexible PTO, requiring a minimum of one day off per quarter, totaling ten days a year to promote mental well-being.

• Recognition of 11 Federal Holidays, with an additional day for both Black Friday and Christmas Eve (for U.S. employees only).

• Health, Dental, and Vision Insurance.

• 401k with employer matching (for U.S. employees only).

• Reimbursement for coworking space and work-from-home setup.

• Company Offsites for planning, team-building, and networking.