About the Role
The role involves developing robust machine learning models, improving existing systems, and integrating AI capabilities into core products while ensuring performance, scalability, and maintainability.
Responsibilities
- Design and deploy scalable machine learning models
- Collaborate with research teams to transition prototypes into production
- Optimize model inference speed and resource efficiency
- Monitor model performance and implement retraining pipelines
- Work with data scientists to refine feature engineering processes
- Ensure models comply with data privacy and ethical guidelines
- Troubleshoot and resolve issues in live machine learning systems
- Contribute to architecture decisions for AI infrastructure
- Evaluate new machine learning frameworks and tools
- Improve data pipelines supporting model training and inference
- Lead code reviews and set engineering standards for ML components
- Document model behavior, assumptions, and limitations
- Support deployment automation and CI/CD for ML workflows
- Collaborate on A/B testing strategies for model rollouts
- Communicate technical trade-offs to non-technical stakeholders
Nice to Have
- Master's or PhD in a quantitative discipline
- Experience with natural language processing or computer vision
- Contributions to open-source machine learning projects
- Prior work in startup or high-growth environments
- Familiarity with edge deployment of ML models
- Experience mentoring junior engineers
- Knowledge of reinforcement learning techniques
- Published research in machine learning or AI conferences
Compensation
Competitive salary and equity package
Work Arrangement
Remote with flexible hours
Team
Small, cross-functional team focused on AI-driven solutions
Our Tech Stack
We use PyTorch for model development, Kubernetes for orchestration, and GCP for infrastructure. Our data layer is built on BigQuery and Pub/Sub, with Airflow managing workflows.
Growth Opportunities
Engineers are encouraged to lead initiatives, present at team summits, and contribute to strategic planning. Career paths include technical leadership and architecture roles.
Inclusion Statement
We welcome applicants from all backgrounds and experiences. Our hiring process emphasizes fairness, accessibility, and respect for individual perspectives.
Available for qualified candidates
