Responsible AI Engineering Manager Full-time

#LI-GM

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 guidelines, best practices for responsible AI development and technical training.
• Staying updated with current AI trends, ethical considerations, and technological advancements.
• Assisting in the identification and correction of biases in datasets and AI models.
• Documenting AI development processes and maintain a transparent record of decisions and methodologies used.

Travel may be required for this role. The amount of travel will vary from 0 to 100% depending on business need and client requirements.

Here’s What You Need:
• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related technical fields.
• Manager experience: 6-8 years
• Senior Manager: 8-10 years
• Experience in developing and deploying machine learning models and AI solutions. At least 2 from the following: Statistics and Probability Theory, Regression Modelling, Clustering Methods, Deep Learning, Neural Networks, Natural Language Processing, Text Mining, Computer Vision, Image Recognition, Time Series Forecasting, Machine Learning Visualization Tools, Tree Ensembles
• Proficiency in programming languages like Python, R, or Java. Familiarity with AI and machine learning frameworks (e.g., TensorFlow, PyTorch). Experience on big data technologies and tools (e.g., Hadoop, Spark).
• Experience with database management and data processing.
• Understanding and working knowledge of cloud services and platforms (e.g., AWS, Azure, Google Cloud) related to AI.
• Demonstrated ability to work with complex datasets and perform data preprocessing and analysis.
• Strong problem-solving and analytical skills.
• Ability to work collaboratively in a team environment and communicate effectively with team members.
• Commitment to ethical AI development and continuous learning in the field.
• Ability to manage multiple projects and priorities in a fast-paced environment.
• Excellent documentation and presentation skills for technical and non-technical audiences.

Bonus Points If You Have:
• Additional courses or training in areas related to responsible AI, ethics in technology, or similar fields are beneficial.
• Certifications in AI, machine learning, or data science.
• Prior experience in projects focused on ethical AI or AI for social good.
• Knowledge of AI ethics, data privacy, and regulatory frameworks.
• Experience with AI model interpretability and explainability tools. Specialized visualization techniques (D3.js, ggplot etc.)
• Project Management Experience
• Linguistic proficiency (to a reasonable business level) in a language other than English

Equal Employment Opportunity Statement

All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law.

Job candidates will not be obligated to disclose sealed or expunged records of conviction or arrest as part of the hiring process.

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