About the Role
The Machine Learning Product Engineer will bridge the gap between data science and software engineering by building robust, scalable machine learning systems that power product features and improve user experiences.
Responsibilities
- Develop and optimize machine learning models for real-world product integration
- Collaborate with cross-functional teams to define product requirements
- Translate research concepts into scalable production systems
- Monitor model performance and implement updates as needed
- Design data pipelines to support training and inference workflows
- Work closely with data scientists to refine model accuracy
- Ensure models meet latency, scalability, and reliability standards
- Integrate machine learning components into existing software platforms
- Conduct A/B testing to evaluate model impact on user outcomes
- Maintain documentation for models and system architecture
- Troubleshoot issues in deployment and production environments
- Apply software engineering best practices to ML systems
- Optimize inference speed and resource utilization
- Stay current with advancements in machine learning frameworks
- Support ethical AI practices in model development
- Participate in code reviews and system design discussions
- Define metrics to track model effectiveness over time
- Collaborate on feature engineering and selection processes
- Refactor legacy ML components for improved maintainability
- Contribute to technical roadmap planning for AI features
- Ensure compliance with data privacy and security policies
- Work with product managers to prioritize ML initiatives
- Assist in defining success criteria for ML-powered features
- Support continuous integration and deployment pipelines
- Evaluate third-party tools and libraries for ML integration
Nice to Have
- Master’s degree in a technical field
- Experience with large-scale data processing frameworks
- Hands-on work with transformer models or deep learning
- Prior role in a product-focused ML team
- Contributions to open-source ML projects
- Experience with model monitoring and observability tools
Compensation
Competitive salary with equity and performance bonuses
Work Arrangement
Hybrid remote with office availability in select locations
Team
Collaborative product development team focused on AI-driven solutions
About the Role
This position sits at the intersection of machine learning and product development, focusing on turning experimental models into reliable, user-facing features. The engineer will work across the full development cycle, from prototyping to deployment and long-term maintenance.
Impact
Deliver machine learning capabilities that directly influence product decisions and customer outcomes. Success will be measured by model accuracy, system reliability, and positive user feedback.
Available for qualified candidates
