Lead AI / ML Engineer

Accenture PLC; Redmond; Sur place; AUD 90 000 - 130 000; Plein temps

Résumé du poste

Accenture PLC seeks an experienced Responsible AI Engineer to help deliver innovative and responsible AI solutions for clients. You will develop state-of-the-art models, tackle issues of bias and transparency, and ensure privacy and ethics are embedded throughout projects. Strong communication with clients and colleagues is essential.

You’ll work across the full AI lifecycle, collaborating with teams to push the boundaries of responsible AI while delivering practical business impact.

Qualifications

• At least 1 year of experience with responsible AI concepts.
• Experience in client-facing environments is preferred.
• Ability to liaise with clients and technical teams.

Responsabilités

• Develop and implement AI models with ethical and responsible practices.
• Assess and apply RAI dimensions (bias, fairness, robustness, explainability).
• Mitigate risks and support client conversations and proposals.
• Maintain and optimize AI systems for ethical standards.
• Contribute to full AI development lifecycle from data prep to deployment.

Connaissances

AI models

Responsible AI

Bias & Fairness

Explainability

Description du poste

We are:

Accenture’s Global Responsible AI team within the Global Data & AI Practice. AI is becoming more pervasive, more powerful and more accessible. With these new opportunities come increased risks. We work with leading organizations to ensure AI is designed, built and deployed in a manner that engenders trust and adheres to laws, regulations and ethical norms. Our Responsible AI strategy will enable us to embed responsibility into all of Accenture’s data and AI activities. We’re developing and deploying differentiated IP and Responsible AI solutions with our ecosystem partners. We’ll be engaging regulators to help shape the policy agenda, conducting pioneering research with academia and offer training and resources to our clients through the Responsible AI Academy. The risks of AI are real and well- known. Let’s help our clients turn those risks into opportunities.

You are:

We’re looking to grow our Responsible AI team and if you’re an experienced RAI Engineer with a Responsible AI background, we’d love to hear from you.

As a Responsible AI Engineer, you’ll be experienced in building state of the art models to solve difficult business challenges. But you’ll also have at least a year’s experience looking at responsible aspects such as AI model Fairness, Transparency, Explainability, Robustness, Soundness and Privacy – preferably gained in a client-facing environment.

You’ll be a problem solver who is passionate about all things data. You’ll be excited by difficult modelling challenges, and you’ll enjoy working with like-minded people who thrive on pushing the boundaries of the possible. You’ll be an outstanding technical specialist with the strong communication skills needed to liaise with your clients and your colleagues.

At the forefront of the industry, you’ll help make our Responsible AI vision a reality for clients looking to better serve their customers and operate always-on enterprises. We’re not just focused on increasing revenues – our technologies and innovations are making millions of lives easier and more comfortable. But above all, we’re doing this responsibly and inclusively – to make sure AI technology is used equitably and in a way that is both ethically and technically sound.

The work:

You’ll be a key player helping to deliver outstanding work for our Responsible AI clients. Some of the areas you’ll be working in include:

• Developing and implementing AI models and solutions, focusing on ethical and responsible practices.

• Detecting, evaluating and applying relevant RAI dimensions (bias, fairness, robustness explainability etc.) in AI systems; work on mitigating the identified risks. Supporting client sales conversations and proposal preparation

• Optimizing and maintaining existing AI systems for enhanced performance and adherence to ethical standards.

• Participating in the full AI development lifecycle, including data preparation, design, coding, testing, deployment, and support.

• Contributing to the development of internal