AI Engineer
Skills
About This Role
Responsibilities
- Model Development:
- Design, train, and fine-tune machine learning and deep learning models for different applications.
• Data Pipeline Management
Build and maintain robust data pipelines used for model training and inference.
• Deployment & Integration
- Deploy AI models into production systems while ensuring scalability, reliability, and performance.
- Optimization:
- Continuously improve model accuracy, latency, and efficiency through experimentation and tuning.
- Collaboration:
- Work with cross-functional teams to understand business needs and convert them into technical AI solutions.
• Monitoring & Maintenance
Develop monitoring processes to track model performance and detect model drift.
• Research & Innovation
Stay updated with the latest AI/ML advancements and apply relevant technologies to enhance products.
• Compliance & Ethics
Ensure AI solutions follow ethical standards, data privacy regulations, and security best practices.
Requirements
and Skills
Education
- Bachelor s or Master s degree in
- Computer Science, Artificial Intelligence, Machine Learning, Data Science, or related field
- .
Experience
- 5+ years of overall professional experience
- , including
- 2+ years in AI/ML engineering or similar roles
- .
- Hands-on experience with
- machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn
- .
- Proven experience building
- end-to-end AI solutions from data collection to deployment
- .
Technical Skills
- Strong programming skills in
Python
- (knowledge of
- C++ or Java
- is a plus).
- Experience with
- cloud platforms
- such as AWS, Azure, or Google Cloud Platform.
- Knowledge of
- containerization tools
- like Docker and Kubernetes.
- Familiarity with
- MLOps tools and practices
- .
- Knowledge of
- NLP, computer vision, or reinforcement learning
- is preferred.
Core Competencies
- Ability to
- prioritize work and meet commitments
- aligned with organizational goals and project timelines.
- Strong capability to
- manage complex technical challenges
- .
- Accountability for
- delivering high-quality results
- and meeting commitments.
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