Job Description
Join NeuroSync Technologies at the forefront of responsible AI development. As our AI Ethics Specialist, you'll shape the future of ethical machine learning by embedding fairness, transparency, and accountability into our cutting-edge systems. This pivotal role bridges technology and humanity, ensuring our innovations align with societal values while driving business excellence.
We're seeking a visionary professional to lead our ethics framework development, collaborate with cross-functional teams, and pioneer industry standards. If you're passionate about creating AI that serves humanity and want to work in Austin's vibrant tech ecosystem, this is your opportunity to make history.
Responsibilities
- Develop and implement comprehensive AI ethics frameworks aligned with emerging regulations and industry best practices
- Conduct algorithmic bias audits and fairness assessments across ML models and datasets
- Collaborate with engineering teams to integrate ethical safeguards into product development lifecycles
- Create stakeholder communication materials translating complex ethical concepts into actionable insights
- Lead cross-functional ethics committees and drive organizational adoption of responsible AI principles
- Research emerging ethical challenges in AI and propose proactive mitigation strategies
- Mentor junior team members on ethical AI methodologies and industry trends
Qualifications
- Master's degree in Computer Science, Ethics, Philosophy, or related field with 5+ years of AI/ML experience
- Proven expertise in algorithmic fairness, bias mitigation, and ethical AI frameworks (e.g., EU AI Act, NIST RMF)
- Strong background in statistical analysis and experimental design for bias detection
- Experience developing organizational policies and governance structures for responsible AI
- Exceptional communication skills with ability to articulate complex ethical concepts to diverse audiences
- Published research or thought leadership in AI ethics or responsible innovation
- Proficiency with Python and ML frameworks (TensorFlow, PyTorch) for bias analysis
- Track record of successful stakeholder engagement across technical and non-technical teams