Accenture's Global Responsible AI team within the Global Data & AI Practice is looking to grow our Responsible AI team. If you're experienced in Monitoring & Compliance with a Responsible AI background, we'd love to hear from you.
You are: As a Responsible AI Monitoring & Compliance professional, you'll be experienced in ensuring that AI systems are developed, implemented, and maintained in a way that mitigates risks associated with AI. You should have at least a year's experience in responsible aspects such as AI model Fairness, Transparency, Explainability, Robustness, Soundness, and Privacy – preferably gained in a client-facing environment.
You'll bring diverse expertise in monitoring AI systems, machine learning model risk management, and applying regulatory requirements to frameworks and technical tools. You'll be an outstanding technical specialist with the strong communication skills needed to liaise with your clients and 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 focused on increasing revenues while ensuring 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:
Configuring, deploying, and monitoring AI systems on cloud and on-premise environments Monitoring AI systems to identify and mitigate responsible AI dimensions like bias, fairness, robustness, model security, and data security Designing, developing, and deploying AI Operations tools and frameworks – MLOps, LLMOps, and DevOps Setting up systems to detect RAI-related anomalies in data or AI; monitoring and sending alerts as needed Optimizing and maintaining existing AI systems to follow local RAI laws, regulations, and technical guidelines Working with functional teams to convert the business meaning of RAI laws, regulations, and ethical standards to technology Contributing to the development of internal guidelines and best practices for responsible AI deployment and monitoring Staying updated with current AI trends, ethical considerations, and technological advancements 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 designing, developing, and deploying machine learning models and AI solutions. Knowledge of model risk and experience in Model Risk Management. Experience auditing risk functions Experience in working on cloud (AWS, Azure, GCP) and on Data & AI technologies. Proficiency in programming languages like Python, R, or Java. Knowledge of standard IT operations including MLOps, LLMOps, and DevOps. Familiarity with cloud deployment (infrastructure as code) and monitoring functions (ex: Cloud watch on AWS). 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. Ability to independently prioritize efforts based on situational awareness. 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: Strong focus on courses or training in areas related to responsible AI, ethics in technology, or similar fields are beneficial. Certifications in AI, machine learning, risk & compliance, or data science. Business background on RAI principles, Ethical AI, laws, and regulations. Prior experience in projects focused on ethical AI or AI for social good. Knowledge of RAI laws, regulations, and the ability to interpret and apply using technologies. Knowledge of AI ethics, data privacy, and regulatory frameworks. Experience with AI model interpretability and explainability tools. Linguistic proficiency (to a reasonable business level) in a language other than English.
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