About the Role
The role involves leading the design and implementation of scalable AI solutions, mentoring engineering teams, and driving innovation in machine learning applications.
Responsibilities
- Lead the architecture and deployment of AI models in production environments
- Collaborate with research teams to transition prototypes into scalable systems
- Mentor junior engineers in best practices for machine learning engineering
- Design data pipelines to support training and inference workflows
- Optimize model performance for latency, accuracy, and cost efficiency
- Evaluate emerging AI frameworks and tools for integration potential
- Ensure compliance with data privacy and security standards
- Drive continuous integration and deployment for ML pipelines
- Work closely with product teams to define AI-driven features
- Troubleshoot and resolve issues in live AI systems
- Contribute to technical documentation and system design specs
- Participate in code reviews and maintain high code quality standards
- Monitor model behavior and implement retraining strategies
- Support ethical AI practices and bias mitigation techniques
- Lead technical planning for AI roadmap initiatives
- Coordinate with DevOps for infrastructure needs
- Implement model explainability and monitoring tools
- Stay current with advancements in AI and deep learning
- Facilitate knowledge sharing across engineering teams
- Ensure scalability and reliability of AI services
Nice to Have
- Master’s or PhD in a technical field
- Publications or contributions to AI research
- Experience with large-scale data processing frameworks
- Leadership in open-source machine learning projects
- Prior work in high-growth startups or tech firms
- Hands-on experience with transformer models
- Knowledge of reinforcement learning techniques
- Experience with edge deployment of AI models
- Contributions to AI ethics or responsible AI initiatives
- Track record of patent filings or technical innovations
Compensation
Competitive salary with performance-based incentives
Work Arrangement
Fully remote with flexible hours
Team
Cross-functional team of engineers, data scientists, and product specialists
Tech Stack
- Primary languages: Python, SQL
- Frameworks: PyTorch, TensorFlow, Hugging Face
- Cloud: Google Cloud Platform, Kubernetes, Docker
- ML tools: MLflow, Kubeflow, Vertex AI
- Data: BigQuery, Apache Beam, Pandas
Culture & Values
- Emphasis on ownership and initiative
- Data-driven decision making
- Inclusive collaboration across teams
- Commitment to continuous learning
- Transparency in communication
Available for qualified candidates
