Remote Senior Software Engineer

Summary

Join Swapcard, the leading AI-powered event platform, as Senior Software Engineer, Machine Learning. You will be part of the Swapcard Lab team, focusing on developing and maintaining our recommendation system and meetings generator. The ideal candidate should have experience in Python, data models, machine learning models using DBT, and orchestrating workflows with Dagster or Argo Workflows.

Requirements

• Proficient in Python, with solid understanding and practical experience beyond basic familiarity
• Experience in working with data models, building specific machine learning models using DBT, and orchestrating workflows with Dagster or Argo Workflows for example

Responsibilities

• Developing and Implementing ML architecture: Involvement in designing ML models to generate new, valuable content or features for the product
• Data Analysis and Interpretation: Turning complex data into actionable insights is crucial for guiding the development of features that meet user needs and enhance the product's value proposition
• Cross-functional Collaboration: Working closely with product managers, engineers, and other stakeholders to ensuring that ML initiatives align with the overall product strategy and business goals
• Advocating for Technical Excellence: Pushing for high standards in code quality, security, and performance, and maintaining these through code reviews and best practices
• Solving Complex Problems: Taking on high-level technical challenges and driving solutions that have a broad impact on the team and product
• Operational Support: Participating in war-room to troubleshoot and resolve critical issues

Preferred Qualifications

Preferred ML experience: Proven success in designing and optimizing ML services, with a strong emphasis on diagnosing and preventing performance issues

Benefits

• Generous Paid Time Off to ensure you have time for what matters most
• 100% of your health insurance contribution paid by Swapcard
• Work-from-home budget (one-off contribution for equipment in addition to your initial equipment setup)
• Co-working space budget to support remote work in professional environments
• Learning budget to help you develop new and existing skills
• Mental health care initiatives to support your well-being