About the Role
Design and implement production-grade AI solutions that bridge research prototypes with deployable software, ensuring robustness and performance in live environments.
Responsibilities
- Develop and maintain core AI infrastructure components
- Translate research models into scalable production services
- Collaborate with researchers to refine model requirements
- Optimize inference pipelines for latency and throughput
- Design APIs for AI-powered features
- Ensure system reliability under variable load conditions
- Monitor model performance in production settings
- Implement automated testing for machine learning workflows
- Support deployment of models across multiple environments
- Troubleshoot issues in distributed AI systems
- Contribute to architectural decisions for new features
- Enforce security practices in AI service design
- Document technical designs and system behavior
- Mentor junior engineers on best practices
- Evaluate third-party tools for integration potential
- Participate in code reviews and system design discussions
- Improve observability of AI components
- Work closely with product teams to define feature scope
- Maintain up-to-date knowledge of AI advancements
- Drive improvements in development tooling
- Ensure compliance with data privacy standards
- Balance innovation with technical debt management
- Refactor legacy systems for better maintainability
- Assist in defining service level objectives
- Contribute to incident response procedures
Nice to Have
- Advanced degree in a technical field
- Experience with large language models
- Contributions to open-source machine learning projects
- Prior work in AI product development
- Knowledge of natural language processing
- Experience with model quantization or compression
- Familiarity with edge deployment constraints
- Background in MLOps practices
- Published research in AI-related domains
- Leadership in technical architecture planning
Compensation
Competitive salary and equity package
Work Arrangement
Remote with flexible hours
Team
Small, cross-functional team focused on rapid iteration
About the Role
This position sits at the intersection of machine learning and software engineering, focusing on turning experimental models into reliable, user-facing systems. You will work across the stack to ensure AI components are efficient, maintainable, and aligned with product goals.
What We Value
Practical problem solving, ownership of technical outcomes, clear communication, and a commitment to building systems that last. We prioritize candidates who can navigate complexity without sacrificing clarity.
Available for qualified candidates
