AI / ML Engineer

About the Role

As an AI/ML Engineer at Accenture, you will develop and implement cutting-edge applications and systems leveraging AI tools and Cloud AI services. You will be responsible for building production-ready applications with robust cloud or on-prem pipeline integration. A key aspect of this role involves applying Generative AI (GenAI) models as part of solution development, which may include deep learning, neural networks, chatbots, and image processing.

This role requires strong analytical and problem-solving skills, with a focus on implementing generative AI models to derive actionable business insights. You will collaborate with multi-functional teams to understand business challenges, formulate hypotheses, and validate them using data. You will also contribute to defining AI project requirements and objectives, ensuring alignment with broader business goals.

Responsibilities include conducting research to stay abreast of the latest advancements in generative AI, machine learning, and deep learning, and identifying opportunities for integration into products and services. You will optimize existing GenAI models for enhanced performance, scalability, and efficiency, while ensuring data quality and accuracy.

A significant part of this role involves leading the design and development of prompt engineering strategies to maximize the performance and output of our GenAI models. This includes implementing advanced Natural Language Processing (NLP) techniques and prompt engineering methodologies to boost the capabilities of our GenAI models. You will also determine the most effective prompt generation processes to foster innovation in AI technology, working closely with AI researchers and developers.

Experience with cloud-based platforms such as AWS, Azure, or similar is essential. Proficiency in handling diverse data formats and sources through Omni Channel for Speech and voice applications, particularly within conversational AI, is also required. Prior statistical modeling experience and demonstrable experience with deep learning algorithms and neural networks are key.

You will be responsible for developing clear and concise documentation, including technical specifications and user guides, to articulate complex AI concepts to both technical and non-technical audiences. Contributing to the establishment of best practices and standards for generative AI development within the organization is also expected.

Professional & Technical Skills:

• Solid experience developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs.
• Proficiency in Python and experience with machine learning libraries and frameworks like TensorFlow, PyTorch, or Keras.
• Strong knowledge of data structures, algorithms, and software engineering principles.
• Familiarity with cloud-based platforms and services (AWS, GCP, Azure).
• Experience with natural language processing (NLP) techniques and tools (SpaCy, NLTK, Hugging Face).
• Familiarity with data visualization tools and libraries (Matplotlib, Seaborn, Plotly).
• Knowledge of software development methodologies such as Agile or Scrum.
• Excellent problem-solving skills and the ability to think critically and creatively to develop innovative AI solutions.

Additional Information:

• A degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field is required; a Ph.D. is highly desirable.
• Strong communication skills are essential for conveying complex technical concepts effectively to a diverse audience.
• A proactive mindset and the ability to work independently and collaboratively in a fast-paced, dynamic environment are crucial.
• Minimum of 5 years of real-time experience in Machine Learning.
• 15 years of full-time education is mandatory.