AI Research Engineer

Accenture•San Francisco, CA

1d•$28 - $94•Hybrid

About The Position

The Accenture Digital Experiences R&D Group advances the frontiers of human-machine interaction and human-centered computing. Our applied research explores how emerging technologies like Artificial Intelligence, ubiquitous computing, affective computing, neuro-sensing, and Augmented Reality can address business problems and transform human interaction with technology. We balance contributing to current client work with R&D for future client offerings. Recent projects include enhancing human-AI collaboration, combining AI with affective computing and neuroscience for customer engagement insights, creating AI-driven tools for collaborative document creation, and developing frictionless Human-AI experiences through physical, spatial, and affective computing.

Requirements

Bachelor's degree or equivalent (minimum 12 years) work experience in Human-Computer/Human-AI/Human-Robot Interaction, Computer Science, Artificial Intelligence, Computational Design, Cognitive Science, EE, User Experience Research, or a related field. (If Associate’s Degree, must have minimum 6 years work experience)
Minimum of 2 years of experience conducting advanced R&D engineering related to AI, HCI, HRI, or Computational Design.
3 years of experience creating rapid prototypes that apply and test new ideas related to the interaction of emerging technologies and people’s experiences.
Proficiency in software development principles and common programming languages (such as Python, JavaScript).
Proficiency in deep learning frameworks (such as TensorFlow or PyTorch).
Experience in system programming (e.g., ROS2, Shell scripting, etc.) is highly desirable.
Understanding MLLM and VLM architectures, prompt engineering techniques, and Agentic processing stacks.
Expertise with user-centered design practices and user experience research methodologies such as usability testing, interviews, focus groups, etc.
Experience with data annotation or human-in-the-loop systems.
Familiarity with cloud computing environments (e.g., AWS, GCP, Azure).
Experience with code validation, testing, and debugging.
Proven ability to create a project plan and execute against it.
Proven ability to work energetically within a high-performance team.
Proven ability to work creatively and analytically in a problem-solving environment.
Excellent communication (written and oral) and interpersonal skills.
Ability to embed in client-delivery teams as needed, and willingness to travel to do that if needed.

Nice To Haves

MS with experience in Human-Computer/Human-AI/Human-Robot Interaction, Computer Science, Artificial Intelligence, Computational Design, Cognitive Science, EE, User Experience Research, or related field.
Familiarity with building applications with hardware such as biosensing wearables, robotic systems, AR/XR devices, eye-tracking and the like.

Responsibilities

Create rapid prototypes to test and illustrate Labs’ business hypotheses about how AI and emerging tech can transform knowledge work, decision-making, and human-machine collaboration in enterprise contexts.
Support senior researchers in scoping, defining, executing, and communicating research initiatives.
Support development of internal and external thought leadership in various formats (blogs, white papers, videos, research conferences, etc.).
Help generate unique intellectual property (e.g., patents, tools).
Participate in client workshops and client-facing projects, applying expertise to real-world client needs.
Develop technical prototypes embodied in digital and hardware (robotic systems, AR/XR headsets, biosensing wearables, etc.) that explore, test, and communicate the ways that emerging technologies can transform various activities and realms of experience.
Apply technical skills in a client-delivery team.
Define and execute research projects within the group’s overall agenda.
Shape and build on ideas developed with business stakeholders and managers to produce high quality documents and presentations.
Manage and execute projects that combine prototype development, qualitative and quantitative research, and thought leadership.
Collaborate with an interdisciplinary ecosystem of researchers, engineers, consultants, academic partners, and business stakeholders.
Participate in their research community by building relationships, publishing about their work, and building relationships with external researchers.
Synthesize insights across a range of disciplines, including hardware, software, social and behavioral science, and economics.