Principal Software Development Engineer for Machine Learning

About the Role

Key Responsibilities

• Own the architectural design and implementation of sophisticated AI systems and agentic AI capabilities, focusing on advanced patterns such as tool calling, supervisor agents, multi-agent architectures, and human-in-the-loop integration.
• Ensure solutions are highly scalable, performant, and resilient in production environments, defining technical roadmaps and standard methodologies for ML system development and MLOps.
• Architect, implement, and deploy secure, RESTful web services in Python and Kubernetes, designing robust, multi-tenant runtime architectures for fast inference and scaling to millions of users.
• Lead the development and deployment of Python and Spark-based data pipelines for collecting, joining, transforming, and loading large-scale datasets essential for model training and inference.
• Provide technical leadership and guidance to fellow engineers, fostering a culture of engineering excellence, advocating for software development standard methodologies, and participating in design reviews and code quality initiatives.
• Collaborate multi-functionally to translate requirements into technical designs and take ownership of high-quality solutions.
• Apply and advance industry-standard software engineering practices, including automation, observability, scalability, and MLOps, to deliver clean, maintainable, and testable code.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related technical field.
• 8 or more years of experience in production-level Software Development.
• 4 or more years of experience in Python, with a track record of shipping production code and systems.
• 4 or more years of experience building scalable data pipelines and working with large-scale datasets.
• 4 or more years of proven experience deploying production services to cloud platforms (e.g., AWS, Azure, GCP) and using containerization technologies (e.g., Docker, Kubernetes) for MLOps.
• Deep technical expertise in the engineering, deployment, and MLOps of advanced machine learning solutions such as generative models, LLMs, RAG, and AI agents.
• Strong understanding of scalable distributed systems, performance optimization, database technologies (e.g., PostgreSQL, Redis), and robust API development.
• Proven ability to design, implement, and analyze efficient algorithms for complex problems.
• Experience building flexible, reusable, and well-documented software components with comprehensive testing strategies in a continuous deployment environment.
• Excellent communication and collaboration skills.

Nice to Have

• MS/PhD degree in Computer Science or Engineering.
• Additional expertise in advanced ML models and AI agent frameworks.
• Experience with industry-standard MLOps tools and practices.

Qualifications

• Educational background with a Bachelor's degree in a relevant technical field; MS or PhD preferred.

Benefits & Perks

• Competitive salary with pay ranges based on location and experience.
• Eligibility for Workday Bonus Plan, role-specific commission/bonus, and annual stock grants.
• Flexible work arrangements combining in-person and remote work, with at least 50% in-office time each quarter.
• Comprehensive benefits package (details available during hiring).