About the Role
Lead the design and implementation of machine learning systems that enhance product capabilities and customer experiences. Guide technical direction, mentor engineers, and align ML initiatives with business goals.
Responsibilities
- Lead the development of scalable machine learning models for real-time applications
- Define technical roadmaps for ML infrastructure and model deployment
- Collaborate with data scientists and software engineers to integrate models into production systems
- Mentor junior engineers and promote best practices in machine learning engineering
- Evaluate and select appropriate algorithms and frameworks for specific use cases
- Ensure models meet performance, latency, and reliability standards
- Work closely with product teams to identify opportunities for ML-driven features
- Monitor model performance and implement retraining pipelines
- Design data preprocessing and feature engineering workflows
- Optimize models for efficient inference at scale
- Conduct code reviews and maintain high engineering standards
- Drive adoption of MLOps tools and practices across teams
- Troubleshoot and resolve issues in distributed ML systems
- Stay current with advancements in machine learning and recommend relevant innovations
- Contribute to architectural decisions for data platforms and model serving infrastructure
- Ensure compliance with data privacy and security requirements
- Facilitate knowledge sharing through documentation and technical presentations
- Collaborate on A/B testing frameworks for model evaluation
- Support the deployment of models across multiple environments
- Balance technical debt with rapid iteration needs
- Promote reproducibility and version control in ML workflows
- Work with cross-functional stakeholders to gather requirements
- Improve model interpretability and monitoring capabilities
- Help define success metrics for ML-powered features
- Foster a culture of experimentation and data-driven decision-making
Compensation
Competitive salary with equity and performance bonuses
Work Arrangement
Hybrid work model with flexible remote options
Team
Part of the core data science and engineering team focused on intelligent customer engagement systems
What We Value
- Technical excellence paired with collaborative problem-solving
- Initiative in identifying and addressing system limitations
- Clear communication across technical and non-technical audiences
- Commitment to ethical AI and responsible model development
- Curiosity and continuous learning in fast-evolving domains
Benefits
- Comprehensive health insurance coverage
- 401(k) plan with company matching
- Flexible paid time off policy
- Parental leave and family support programs
- Professional development stipend
- Remote work equipment allowance
- Mental health and wellness resources
- Inclusive employee resource groups
Available for qualified candidates
