Gen Ai Workflow Designer

Year    KA, IN, India

Job Description

About the Role




The

Gen AI Workflow Designer

is a key member of DNEG's Generative AI team, responsible for designing, refining, and maintaining efficient workflows for deploying audiovisual GenAI models across production and R&D environments. Working primarily in

ComfyUI

, this role focuses on building and optimizing workflows that enable artists, supervisors, and technical teams to explore, prototype, and deliver high-quality generative content efficiently and responsibly.


You will collaborate closely with DNEG's research, creative, and pipeline teams to ensure these workflows are robust, scalable, and aligned with studio production needs.

Key Responsibilities



Design and maintain efficient, functional workflows for deploying audiovisual Generative AI models, primarily using

ComfyUI

. Identify, evaluate, and integrate emerging GenAI tools and technologies from both open- and closed-source ecosystems. Collaborate with research, pipeline, and creative teams to develop, test, and refine workflow templates that maximise performance and creative flexibility. Experiment with new model and tool combinations to enhance existing pipelines and introduce innovative approaches. Build templated workflows tailored to specific production or creative needs, and collaborate with DevOps teams to transition them into scalable, cross-platform solutions. Work with the GenAI Pipeline team to maintain and improve DNEG's custom ComfyUI environment. Assess and recommend alternative model deployment platforms while contributing to internal platform development. Onboard and train artists from other disciplines in ComfyUI and related workflow tools, helping expand AI literacy across the studio.

Must Have



Proven expertise in

ComfyUI

, including the creation of custom workflows, nodes, and pipelines using

Python

and

JavaScript

. Experience maintaining and deploying custom ComfyUI environments. Demonstrated ability to integrate existing AI tools and techniques into larger production pipelines. Strong understanding of model deployment platforms and the ability to evaluate new tools and frameworks. Hands-on experience setting up testing environments for model inference and training (Conda, Git, dependency management). Proficiency in

Python/PyTorch

with the ability to adapt and extend existing codebases. Experience collaborating effectively with developers, technical artists, and creative teams. Professional experience testing

photoreal generative models

, ideally for video or time-based outputs. Deep engagement with the wider

Generative AI community

, including open- and closed-source developments. Ability to mentor and onboard artists in ComfyUI and generative workflow usage.

Nice to Have



Previous experience in a

pipeline

,

R&D

, or

technical art

capacity within VFX, animation, or a related creative technology environment. Background in

VFX

,

visual arts

, or

digital production

with a strong technical foundation. Familiarity with AI-driven visual tools such as

Runway

,

Kling

,

Lumalabs

, or similar platforms. Awareness of emerging standards for ethical and transparent AI-assisted production.

Why Join DNEG




At DNEG, we are shaping the future of digital production by combining decades of VFX excellence with the latest advancements in AI and machine learning.

As a

Gen AI Workflow Designer

, you will help define how these technologies are applied within our creative pipelines, enabling new efficiencies and artistic possibilities while upholding the highest standards of visual integrity.


You'll work alongside world-class artists, engineers, and researchers on some of the most ambitious projects in the industry -- contributing directly to how next-generation storytelling is imagined and realized.

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Job Detail

  • Job Id
    JD4781035
  • Industry
    Not mentioned
  • Total Positions
    1
  • Job Type:
    Full Time
  • Salary:
    Not mentioned
  • Employment Status
    Permanent
  • Job Location
    KA, IN, India
  • Education
    Not mentioned
  • Experience
    Year