What is a Explainable AI Engineer?
A Explainable AI Engineer is an Senior level role in the AI sector. It involves handling a range of tasks that may include: XAI, Model Interpretability. This role helps ensure the smooth functioning of AI services within an organization. On average 6-8 years of experience are required.
Key Responsibilities of a Explainable AI Engineer
- Handling issues related to AI operations.
- The Explainable AI Engineer is responsible for handling tasks related to explainable ai engineer functions. They work to ensure effective and efficient delivery of their specific IT services.
- Participating in maintenance, troubleshooting, or process improvement efforts.
- Assisting teams to optimize efficiency and ensure goals are met.
Work Environment
- Work Type: Full-time
- Remote Work: Yes
- Growth Potential: Very High
- Industry focus: Research
Skills You Need
- Proficiency: Understanding of concepts related to AI this can include XAI, Model Interpretability
- Communication Skills: Effective support for stakeholders or team members
Educational Requirements
- Minimum Education: PhD
- Certifications: Consider obtaining a XAI Certificate for career advancement
Salary Information
Expected Salary Range: $135000 to $195000 per year, depending on experience and location.
Mid Level
Senior Level
$195000
How to Get Started
- Make sure you enjoy tasks like XAI, Model Interpretability.
- Obtain relevant education like an XAI degree.
- Apply for Senior positions in the AI field.
Is This Role Right for You?
This role might be a good fit if you:
- Enjoy working in AI and solving related challenges
- Are looking for a stepping stone into a career where your skills need to be XAI, Model Interpretability
- Value Full-time
A Explainable AI Engineer position is an excellent entry point to start a career in AI. With solid education, certifications, and passion, you can make a significant impact.
Personality & Challenges
Ideal Personality: Adaptable, driven, collaborative. Suitable for those who enjoy solving problems related to the role.
Common Challenges: Dealing with role-specific issues, working with teams under deadlines, adapting to technological changes.