AI/ML Computational Science Specialist

Accenture•Kirkland, WA

2d•$59,100 - $205,800•Hybrid

About The Position

As an Artificial Intelligence and Machine Learning Computational Science professional, you will play a pivotal role in formulating real-world problems into practical, efficient, and scalable AI and Machine Learning solutions. You will be responsible for developing and implementing cutting-edge artificial intelligence solutions that drive innovation and enhance performance. You will collaborate with cross-functional teams and leverage your expertise in machine learning, deep learning, and data analysis to solve complex problems and deliver impactful AI-driven solutions.

Requirements

Minimum of 3 years of full-time experience in Data Analysis, Statistics, Machine Learning, or Computer Science
Minimum of 2 years of experience in machine learning, deep learning, or demonstrated proficiency in Natural Language Processing (NLP)
Minimum of 2 years of experience with AI/ML and cognitive services provided by at least one cloud service provider
Minimum of 1 year of experience in building Conversational AI applications using cloud-based services and in orchestrating AI/ML services for building a complete solution
Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate’s Degree, must have minimum 6 years work experience)

Nice To Haves

Hands-on involvement with speech-to-text, text-to-speech, and chatbot technologies

Responsibilities

Collaborate with stakeholders to engineer innovative solutions for new system roll-outs, enhancements, and maintenance of existing applications, ensuring adherence to programming standards.
Develop system specifications, create test plans, and conduct project and issue management for the assigned scope of work.
Design/Build solutions using AI services and machine learning models to address unique use cases, employing cutting-edge techniques and methodologies.
Utilize machine learning and advanced AI techniques to extract valuable insights from complex datasets and solve intricate problems.
Deploy trained models into production environments, ensuring scalability, reliability, and optimal performance, while integrating seamlessly with existing systems and applications.
Design and implement agents and multi-agent architectures to optimize client workflows.