Job Overview
The AI/ML Engineer is responsible for integrating AI capabilities into enterprise platforms, products, and business workflows.
This role focuses on operationalizing AI solutions by integrating AI models and AI services into production systems, and enabling scalable, secure, and responsible AI adoption across the organization.
Responsibilities
- Lead the development and implementation of complex machine learning models, ensuring they meet project requirements and performance metrics.
- Oversee data preprocessing, cleansing, and management. Develop strategies for data acquisition and utilization to enhance model performance.
- Optimize existing AI/ML models for better efficiency and accuracy. Implement advanced algorithms and techniques to improve system performance.
- Collaborate with data scientists, domain engineers, and product managers to integrate AI/ML solutions into products and services, acting as a liaison between technical and non-technical teams.
- Provide guidance and mentorship to junior team members. Lead project teams as required, ensuring timely delivery and quality of work.
- Engage in ongoing research to stay ahead of the latest trends and developments in AI and ML, proposing and leading innovative projects or experiments.
- Prepare comprehensive documentation and reports on AI/ML projects, including development processes, performance metrics, and deployment strategies.
- Assist in the integration of models into systems:
- Collaborate with software engineers and IT teams to seamlessly incorporate machine learning models into production environments.
- Design and develop APIs or interfaces for model integration, ensuring compatibility with existing systems.
- Optimize model performance for real‑time or batch processing as required by the application.
- Develop automated workflows for model training, testing, and deployment to streamline the integration process.
Qualifications
- 2-5 years of experience in AI and ML development, with a proven track record of successful projects.
- Bachelor's or Master’s degree in Computer Science, Engineering, AI, Mathematics, or a related field.
- Familiarity with the content and application of standards, codes, and guidelines as applicable; knowledge of many basic design techniques and analysis methods.