Software Engineer, AI Data

This role offers the opportunity to design and build scalable, high-performance systems that power next-generation AI data platforms. You will work on mission-critical pipelines that support large-scale model training and evaluation, impacting millions of inference calls and hours of processed data. The role combines software engineering rigor with AI-focused infrastructure, providing a chance to shape technical execution, optimize data workflows, and drive innovation in a fast-paced, high-impact environment. You will collaborate closely with researchers, platform engineers, and other stakeholders to deliver reliable, maintainable, and cost-efficient systems that accelerate AI model development. This is an ideal position for engineers who thrive in a startup-like culture where ownership, technical excellence, and measurable impact are paramount. Accountabilities:

• Architect and implement scalable AI data infrastructure to support model training and evaluation at scale
• Build efficient, self-serve data processing pipelines leveraging cloud services and distributed systems
• Design cost-effective storage, monitoring, and resource management solutions to maximize efficiency
• Lead adoption of cutting-edge ML/AI tools and frameworks to enhance team velocity and system reliability
• Streamline workflows, introduce new tooling, and maintain high-quality documentation for engineering processes
• Troubleshoot and resolve complex technical issues while improving system performance, quality, and cost-efficiency
• Participate in on-call rotations to ensure operational reliability of AI data platforms

• 5+ years of professional software engineering experience with strong Python and SQL proficiency
• Solid understanding of software engineering fundamentals: data structures, algorithms, system design, architectural patterns, and testing strategies
• Experience with RESTful APIs, distributed systems, and containerization (Docker) in cloud environments
• Proven ability to deliver high-quality, maintainable code in collaborative team settings
• Strong communication and stakeholder management skills, with the ability to explain technical concepts clearly
• Startup mindset: able to navigate changing priorities, rapid iteration, and pragmatic decision-making, * Experience with GCP services (BigQuery, GCS, Cloud Run, GKE)
• Familiarity with distributed processing frameworks (Apache Beam, PySpark)
• Knowledge of workflow orchestration tools (Airflow, Prefect, Dagster)
• Background in ML/AI infrastructure, monitoring tools (Datadog), or data engineering roles
• Experience collaborating directly with researchers

• Competitive salary with equity grants and location-adjusted compensation
• Fully remote work with flexible hours and autonomy over work-life balance
• Comprehensive employer-paid health benefits
• Access to cutting-edge AI tools and frameworks, fostering skill growth and innovation
• Collaborative, high-impact environment with opportunities to shape technical strategy
• Professional development opportunities including mentorship, training, and learning resources