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Machine Learning Engineer

Job in Austin, Travis County, Texas, 78716, USA
Listing for: Talentify
Full Time position
Listed on 2026-10-05
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 173000 - 307000 USD Yearly USD 173000.00 307000.00 YEAR
Job Description & How to Apply Below
Position: Staff Machine Learning Engineer

Open — Adobe has a posting for this job. Posted 23 Sep 2026.

This posting

Opens  Talentify has not checked who owns that address. You apply there — Talentify never asks for an account or a CV.

About this job

The Opportunity

Join Adobe’s Brand AI Services team and help define the future of AI-powered creativity
. We are building multimodal and agentic AI systems that enable marketers and creative professionals to ideate, create, understand, and transform content through intelligent AI-powered workflows.

As a Staff Machine Learning Engineer
, you will design and deliver production-grade generative and agentic AI systems that power Adobe Firefly AI Assistant and experiences across Creative Cloud, Adobe Express, Gen Studio, and more.

You’ll work at the intersection of computer vision, generative AI, multimodal learning, and agentic AI
, building systems that understand creative intent, reason across multimodal content, use tools, and orchestrate complex creative workflows. This is a high-impact role focused on building the next generation of AI experiences for millions of creative professionals.

Come create the future with us!

What You’ll Do

  • Lead the design, development, and deployment of multimodal and generative AI systems spanning vision, language, and other modalities.
  • Build and product ionize generative AI models and systems
    , including transformers, diffusion models, LLMs, and vision-language models (VLMs), for content creation, understanding, and transformation.
  • Develop and build agentic AI systems that can reason, use tools, interact with models and services, and complete complex multi-step creative workflows.
  • Build intelligent capabilities for Firefly AI Assistant and Creative Cloud workflows
    , helping creative professionals move from intent and ideas to high-quality creative outcomes.
  • Develop scalable services and APIs that integrate AI and machine learning capabilities into Adobe products.
  • Drive the end-to-end ML lifecycle, including problem formulation, modeling, experimentation, evaluation, deployment, monitoring, and iteration.
  • Partner with engineering, product, design, and research teams to translate customer needs into effective ML solutions.
  • Improve the performance, scalability, reliability, and quality of AI systems operating in high-traffic production environments.
  • Provide technical leadership, mentor engineers, and help raise the engineering and machine learning bar across the team.
  • Identify new opportunities to apply generative and agentic AI to real-world challenges for creative professionals and enterprise customers.

What You Need to Succeed

  • MS or PhD in Computer Science, Machine Learning, or a related field, or equivalent practical experience.
  • 5+ years of experience building and deploying machine learning systems in production.
  • Hands-on experience designing and building agentic AI systems
    , including areas such as tool use, agent orchestration, multi-step workflows, planning and reasoning, retrieval, memory, or human-in-the-loop systems
    .
  • Experience with agent interoperability and tool integration
    , including Model Context Protocol (MCP), function/tool calling, or similar frameworks and protocols.
  • Expertise in computer vision, generative AI, and/or multimodal machine learning
    , with hands-on experience using modern architectures such as transformers, diffusion models, LLMs, or VLMs.
  • Solid foundation in probability, statistics, machine learning, and model evaluation
    .
  • Proficiency in Python and experience with machine learning frameworks such as Py Torch .
  • Experience designing and building scalable APIs, distributed services, or production ML infrastructure
    .
  • Strong software engineering fundamentals, including data structures, algorithms, testing, code quality, and code reviews.
  • Experience with cloud…
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