Senior Machine Learning Engineer

Adobe Systems
San Jose
Workplace: OnsiteFull timeUSD 151,800 - 265,350 annuallyFunction: Data Science & Machine LearningEducation: phdSkills: ["Analytical problem-solving","Quantitative problem-solving","Communication","Collaboration","Relationship-building"]

Build and deploy large-scale machine learning systems for Adobe’s Search, Discovery & Content AI team, powering generative AI agents and intelligent content discovery across Creative Cloud, Document Cloud, and Adobe Express. Design end-to-end ML architectures, optimize and deploy GPU-accelerated models for production scale, and develop high-performance ML pipeline platform features. Partner cross-functionally with product and engineering to translate requirements into technical solutions and keep pace with emerging ML runtimes.

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FursaFursa
Adobe Systems
Adobe Systems
1 day ago

Senior Machine Learning Engineer

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 5 hours agoStatus: Live
Reposted: similar role first listed 9 months ago

Job Summary

Build and deploy large-scale machine learning systems for Adobe’s Search, Discovery & Content AI team, powering generative AI agents and intelligent content discovery across Creative Cloud, Document Cloud, and Adobe Express. Design end-to-end ML architectures, optimize and deploy GPU-accelerated models for production scale, and develop high-performance ML pipeline platform features. Partner cross-functionally with product and engineering to translate requirements into technical solutions and keep pace with emerging ML runtimes.
Location: San Jose
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Design and develop end-to-end large-scale machine learning systems using innovative architectures.
  • •Develop and implement scalable, GPU-optimized modeling algorithms for production environments handling large-scale data.
  • •Build and maintain high-performance, scalable, and maintainable platform features across the complete ML pipeline.
  • •Collaborate with architects, product management, and engineering teams to translate product requirements into technical solutions.
  • •Design and develop runtimes and libraries for emerging ML technologies and contribute to detailed requirements and design documents.

Pay and Benefits

Salary: USD 151,800 - 265,350 annually
Equity and Bonus:Equity

Key Requirements

  • •PhD or master’s degree in computer engineering, Computer Science, Computer Vision, Robotics, or a related field, or equivalent experience.
  • •Deep understanding of generative AI, deep learning, computer vision, and recommendation systems applied to complex problems.
  • •Proficiency with machine learning frameworks and tools such as Scikit-learn, Hugging Face, PyTorch, and PyTorch Lightning.
  • •Experience with cloud technologies and containerization (including Docker) for production deployments.
  • •Proficiency in one or more programming languages, including Python, C++, Java, and Rust.
Experience:Generative AIDeep learningComputer visionRecommendation systems
Education:PhD / Doctorate in Computer Engineering, Computer Science, Computer Vision, Robotics, or related field
Skills:Analytical problem-solvingQuantitative problem-solvingCommunicationCollaborationRelationship-building
Tech Stack:Scikit-learnHugging FacePyTorchPyTorch LightningMachine learning frameworksCloud technologiesDockerContainerizationAWSMicrosoft AzurePythonC++JavaRustGPU-optimized modelingDeep learningComputer visionRecommendation systems

Company Brief

Adobe Systems
Provides creative, marketing, and document management software and cloud services, including Photoshop, Illustrator, Acrobat, and the Adobe Experience Cloud, serving creative professionals, enterprises, and governments worldwide.
Industry: SaaS
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: San Jose, United States
Founded: 1982
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